{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd         ###multigauss2（ノートブック全部）###\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data  = pd.read_csv(\"sensor_data_200.txt\", delimiter=\" \", \n",
    "                    header=None, names = (\"date\",\"time\",\"ir\",\"lidar\"))\n",
    "\n",
    "d = data.loc[:, [\"ir\", \"lidar\"]] #光センサとLiDARのデータだけにする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ir</th>\n",
       "      <th>lidar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ir</th>\n",
       "      <td>109.394583</td>\n",
       "      <td>-13.444661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lidar</th>\n",
       "      <td>-13.444661</td>\n",
       "      <td>23.408107</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ir      lidar\n",
       "ir     109.394583 -13.444661\n",
       "lidar  -13.444661  23.408107"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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oZv2OZprbul63Tt2QQYwZVsXo2ipG1gxiRE0lwwZXMnRwBTVVFdRUllMzqJxBFWVUVZRTWW5UlBsVZWWUlxllZpSVQZkZBnT/WXb/bSb/iU4eVZPrVp4OAClQYCV50zfuf/VTXC4MHVxBfW0V9UOrmFJXw+RRNRwyppaDRw+hovi6NETyyt3Z1dLBpl0tbNndSsPeNhr2tbFjXxt7gg+N+1o72dfWSSLHh7mHP3cKk0bV5HKTCqwUxDqwzOxeYHRImx8NNIa07VxTrbkXlzpBtYYln7U2uvuZedpXbMU6sMJkZkvcfWHUdaRCteZeXOoE1RqWONVaKtQvJSIisaDAEhGRWFBg9W1R1AWkQbXmXlzqBNUaljjVWhJ0DktERGJBLSwREYkFBZaIiMSCAktERGJBgSUiIrEQ68A688wzne7pmXTTTTfd4nxLSZEe81IW68BqbIzLDC8iItkr9WNerANLRERKhwJLRERiQYElIiKxoMASEZFYUGCJiEgsKLBERCQWFFgiIhILCiwREYkFBZaIiMSCAktERGJBgSUiIrGgwBIRkVioiLqAKOxo6Yq6BBEpQnU15VGXUNTUwhIRkVhQYImISCwosEREJBYUWCIiMbG3tZPdLe1RlxEZBZaISEys39HMS9v3RV1GZBRYIiISC6EFlplNMrMHzOxFM1tmZp8Oln/NzJ4zs2fM7M9mNj5Ybmb2XTNbHTx+ZFi1iYhI/ITZwuoErnT3OcBxwGVmNgf4lrsf7u7zgT8AXwnWfzswI7hdAvwwxNpERCRmQgssd9/q7k8F9/cCy4EJ7t6UtNoQwIP75wI3e7fHgRFmNi6s+kREJF7ycg7LzKYCC4DFwf+/bmYbgQ/yWgtrArAx6WmbgmU9t3WJmS0xsyUNDQ1hli0iErnkYx6Auw/0lKIVemCZWS1wB3DFgdaVu3/J3ScBtwCfSmd77r7I3Re6+8L6+vrcFywiUkCSj3lR1xK1UAPLzCrpDqtb3P3OXla5BXhPcH8zMCnpsYnBMhERkVBHCRpwI7Dc3a9JWj4jabVzgRXB/buADwejBY8D9rj71rDqExGJo9LtEAx3tvYTgAuB583smWDZF4GPmdksIAFsAC4NHrsbOAtYDbQAF4dYm4iIxExogeXujwDWy0N397G+A5eFVY+IiMSbZroQEZFYUGCJiEgsKLBERCQWFFgiIhILCiwREYkFBZaIiMSCAktERGJBgSUiIrGgwBIRkVhQYImIxEgJf7uIAktEJE68hKe/VWCJiMSIWlgiIhILiRJOLAWWiEiMJEo3rxRYIiJxkijhxFJgiYjESJcCS0RE4qBL57BERCQO1MISEZFYUGCJiEgsdCYSUZcQGQWWiEiMlPApLAWWiIjEgwJLRCRG1MISEZFYqCi3qEuIjAJLRCRGyssUWDlnZpPM7AEze9HMlpnZp4Pl3zKzFWb2nJn9xsxGBMunmtl+M3smuF0fVm0iInFVbgqsMHQCV7r7HOA44DIzmwPcB8xz98OBl4Crkp6zxt3nB7dLQ6xNRCSWytTCyj133+ruTwX39wLLgQnu/md37wxWexyYGFYNIiLFpnTjKk/nsMxsKrAAWNzjoY8C9yT9f5qZPW1mD5rZifmoTUQkTkp4oovwA8vMaoE7gCvcvSlp+Zfo7ja8JVi0FZjs7guAzwC/MLNhvWzvEjNbYmZLGhoawi5fRCRSycc8gI4uzXQRCjOrpDusbnH3O5OWfwQ4G/ige/dVBe7e5u47gvtLgTXAzJ7bdPdF7r7Q3RfW19eHWb6ISOSSj3kA7Z0KrJwzMwNuBJa7+zVJy88EPgec4+4tScvrzaw8uH8wMANYG1Z9IiJxtL+jK+oSIlMR4rZPAC4EnjezZ4JlXwS+C1QB93VnGo8HIwLfAvy7mXUACeBSd98ZYn0iIrHT0t458EpFKrTAcvdH6H1Ay919rH8H3d2HIiLSh31tpdvC0kwXIiIxYQb7S7iFpcASEYmJMjNa2tXCEhGRAqfAEhGRWCiz0h50ocASEYkJM2N/h67DEhGRAldm0NymFpaIiBS4cjOa9ndEXUZkFFgiIjFRVmbsbVULS0RECly5Gbv3t0ddRmQUWCIiMVFeZrR2JEp2pKACS0QkJsqDbxtu3FuarSwFlohITFSWdwfW5t37I64kGgosEZGYqCzvPmRv2tUywJrFSYElIhITFeVllBm8vFOBJSIiBcyAMUOrWNfYHHUpkVBgiYjEyEHDqxVYIiJS+MYPH8zqV/bR2VV6cwoqsEREYmRK3RDaOhMl2cpSYImIxMjU0UMAWLalKeJK8k+BJSISIxNGVFNdWcaT63dGXUreKbBERGKkvMyYddAwHlu7I+pS8k6BJSISM3PGDWNtQzPbm1qjLiWvFFgiIjFz+MThAPxt5SsRV5JfCiwRkZiZPKqGuiGD+OsKBZaIiBQwM2PB5BE89FIj+9pK56tGKqIuQOJjZWNbyuvOGl0VYiUi8pYZ9fxl+Sv8/tktfOCYyVGXkxehBZaZTQJuBsYCDixy92vN7FvAO4F2YA1wsbvvDp5zFfAxoAu43N3/FFZ9pSyd4MnlPhRiIrkzfUwtk0ZWc+sTLyuwcqATuNLdnzKzocBSM7sPuA+4yt07zey/gKuAz5vZHOACYC4wHviLmc10964Qayxq+QimdPRVj4JMJH1mximHjuHmxzawbMse5o4fHnVJoQstsNx9K7A1uL/XzJYDE9z9z0mrPQ68N7h/LnCbu7cB68xsNXAM8FhYNRarQguqgQxUbxwDLd2fQRxfo0TvxOn13PrEy9z2xEa+dp4CKyfMbCqwAFjc46GPAr8M7k+gO8AO2BQs67mtS4BLACZPLo1mcKriFlSpikPLLNv3vufzC+m1SbSSj3kTJk563WO1gys4blodv3l6M1eddSg1g4p7WELor87MaoE7gCvcvSlp+Zfo7ja8JZ3tufsiYBHAwoULPYelxlqxhlV/ojjI5+t9PrAfBZckH/MOn3/kG455p80ey8OrG/ndM8U/+CLUwDKzSrrD6hZ3vzNp+UeAs4HT3P3AD2AzkPzxYWKwTAZQimHVm2wHehTi+5hck8JLejNzbC2TRlXzf49v4IKjJ2FmUZcUmjBHCRpwI7Dc3a9JWn4m8DngJHdP/p7nu4BfmNk1dA+6mAE8EVZ9xaAQD7CFppjeo5WNbQoteQMz462zx3LTo+tZsmEXR08dFXVJoQnzwuETgAuBU83smeB2FvA9YChwX7DsegB3XwbcDrwI3AtcphGCfSumA7GkbmVjm3728gZvmVHPiJpK/vveFbzWaVV8whwl+AjQW9v07n6e83Xg62HVVCx0wBK1tiTZ4Mpy3r1gAj95dD0PrHyFUw8dG3VJoSjuISVFKKywWt6Q+nZn1+tAWQgUWpLslEPHcPfz2/jPu1dw4ox6KsuLb+Y9BVYJSiecMnm+Ai1/FFpyQEVZGR88bjLf/vNL3PzYBj725mlRl5RzCqwYybR1lW1A5WJ/CrHwKLTkgKMmj+SIScP53/te4p1HjGPM0MFRl5RTxddmLFKZhNXyhra8h1VfDtSSfJPc0XlNge4RgxcdN5X2zgSX/+JpOrsSUZeUU2phFaG4hEF/dcahRRbW+5zpa1dLSwDGjajm4ydO4wd/W8M37lnBv549J+qSckaBFQOpfnqOS1ClIpXXEmaoRfleJu873deo0BKAE2fUs6ahmRsfWcdhE4Zz3oI3zHIXSwqsAleKYZWqUnjNB15jOsGl0BKADx03mZd3NvPZXz/LxJHVLCyCC4oVWEUg2wN3Nuc/dGDMj3SDS6ElFWVl/PNbZ3L1Xcv4xM1L+O1lJzClbkjUZWVFgy4KWCpBkm5YHZgpIfmWjd62pwEA4Unn562fgwwdXMlnz5hFR5dz8U1PsrulPeqSsqIWVoylevCK4sBVjN9xVSjSaW2ppSXjhldz5ekz+frdy/mHny/l5o8dQ1VFedRlZUSBVaAGOuCnElaF/Ak7Dt9xlYpcvceZvO7lDW0KLUnJoeOGcelJh/C9B1Zz1R3P8+3zj4jlrO4KrCJUyEE1kGy/IiRMYb6vmX63V6qhJXLC9NFsb2rlV0s3MXhQOV87dx7lZfEKLQVWAcqmdRXnsOpLMX9R40D7T+W1phJaamUJwLsWTKCtM8EvFr9M0/4Orjl/PoMq4jOUQYFVRDI5yGZ7YI7iINhfzanWE3UgpSqX3zys0BIz4wPHTKa2qoJfPNEdWj+6cCHVg+JxTkuBVWAybV2legDO9YE6le3l8yAZlyBK10Bho/NZko53HjGeIVUV3PDwWj55y1J+dOHCWLS0FFgxks31VlEeyAst1MKQj5aqQkty6dRDx+A4Nzy8jitvf4bvXLCg4M9pKbCKQH8Hy7i0OJLrjMPBNMyWan+vf6AuQoWWpOO0Q8fS3NbFrU+8zJCqCv7zXYdRVsChpcAqILk+BxWXsOqpEMMrn+9lKuet+gucdEJroP1I8TvniPG0dnRx25MbaW7r5NsFPBBDgRUTmcxokY51r+xJa/2+TBszPCfbOSDK8Io68AcKlFyE1kDbkdJw/sJJDK4s59YnXqaptZPrP3RUQQ7EUGDFWF8H1FQOtLkKqHS3m02g5aNFkOuQ6uv9SOd96C9QFFqSK+ccMZ7aqgpufGQtH7zhcW686GhGDhkUdVmvo8AqMgMdcMMKqlT13H8mAZarVle+wimVdQd6H/IRWiKnHjqGIVXlfP+B1bz7h3/n5o8ew6RRNVGX9SoFVoHo7+DZW3dgVF1+uZZtgEXdbZer9zV5O329B/21MHPRQlIrSwCOnVbH8OpKvv3nlzjv+4/y04uP4bCJue3qz5QCq4j0dfDO5qDatHV92s8ZNm5qxvs7UGuuz4XlUtjhP9B7kG6wqGtQ0nXoQcP46jvn8l9/WsEFP36MX15yPPMmRP83WZhDQSRtuQirpq3r33DLRG/bSXdb617Z8+qtUOS7nv721dvPO91Wukh/Joys5uqz51BdWc6Hf/IE6xqboy5JgVXMUjm4ZhtO6cg0wKIMrqiDs799pxtaqYq6m1UKR11tFV98+2w6Ewk+dMNitu7ZH2k96hKMoVyMAsxHQA0kuYZUuhHz2V2Yz27UVF97b6+7ty68vrr1NABDMjFuRDWfP+NQ/uOPyznv+4/yk48czdzx0XQPhhZYZjYJuBkYCziwyN2vNbP3AV8FZgPHuPuSYP2pwHJgZbCJx9390rDqKybpfCLOJqjatqwceCWgavystLd9oK50ggtyG175PtfX23P7e/19hVYYdC5Lkh1cX8vV75zDt/60kvde/xjXXbCAt84Zm/c6wmxhdQJXuvtTZjYUWGpm9wEvAO8GftTLc9a4+/wQayoJfR14MzmophpSAz0n1RBLJ7ggu/DKRTdfrluqA73+3kJLrSzJhyl1Q/jaefP4nz+v5BM3L+Fr583jQ8dNyWsNoQWWu28Ftgb395rZcmCCu98HxPLbLuMsnQNrJiGVzjZTCa90uwuh/yHyuT4HFXaXatPW9aGFVqrUypKeRtYM4itnz+Hav6ziK797gUmjajhpZn3e9p+XQRdBd98CYPEAq04zs6fN7EEzO7GPbV1iZkvMbElDQ0OOKy1OqRxc27asfPUWtnT3k+mgkLAGTOTr/F9/r7u315Rq17BGDMZL8jFv547GqMuhqqKcy0+bwaSRNfzTL57K6+jB0APLzGqBO4Ar3L2pn1W3ApPdfQHwGeAXZjas50ruvsjdF7r7wvr6/CV7XKR7cM5XSOVi3/kazVho+88mtPoKsVRDSyMGo5d8zBtVNzrqcgAYXFnOlW+biQMf/9mTNLd15mW/oY4SNLNKusPqFne/s7913b0NaAvuLzWzNcBMYEmYNZayXARVz21kMuDiwDbSOc+VzcXJ6Qrz3F+25/ZSGYihrj0JQ/3QwVx+6gy+cc9yvvzbF7jm/CNCP9UT5ihBA24Elrv7NSmsXw/sdPcuMzsYmAGsDau+UtHXwTbTsBroedkEWDrBle7gjEylG1bpvq+ZnNsbKLRSDSh9d5Zka96E4bz7yIn8eukmjp02iguOmRzq/sLsEjwBuBA41cyeCW5nmdm7zGwTcDzwRzP7U7D+W4DnzOwZ4NfApe6+M8SUnslSAAAgAElEQVT6SlamI//y9bx0nhNWN126281F12qq2+itrp7dg6l2DaZKXYPSl3fNn8BhE4Zz9V3LeGbj7lD3FVpgufsj7m7ufri7zw9ud7v7b9x9ortXuftYdz8jWP8Od58brHeku/8+rNokdbk6xxWX4MpkO7k+B5jK685VaKUzAEOhJb0pKzM+dep0hldX8vGfPcmW3eHNhqGpmaRXYQ3GyDS4UpXpVFOZBl6YA1YGeq9y1bLUqEHJ1rDBlXz2jFm0tHfxsZ+GNwhDgVViUjkHla+h7emun+5zUgmvbFpm+RpdmU5oqWtQojJxZA3/dOoMlm/by82PbQhlHwoseVW+h7eH3U2YLBczyPesI5/Sed0DXdqgrkEJy/xJI5g9bii3PvEyiYTnfPsKrCKT6VxzUV2Llem+o75+LCq97Xug4A3jgmKFlvTltEPH8vLOFh5dk/uLnBVYUhDyOQoxCskziYQxq0i+uwZztQ0pPkdPHUXdkEFc/btl7G/vyum2FVgxVMzXxGRzfVihnXtLJZgyCa8wX2e6AzAUWtLToIoyLj3pENY2NvONe5bndNsKLCm4Fko24RNmcIX9PqVTeypdg5m2sjRqULI1b8Jwzpp3EDc/toG/r85d16ACq0Bk02oq1hZXLoIrjue54tLNeYBaWdKb9x89mbohg7j2/lU526YCq8jlc869sGR7AM/VLBRhrJvNdgqplaXQkp4GVZTx9nnjWLxuJ0+/vCsn21RgSUbaNi9P6ZbTfUYUXIU2KjCdx1Oh0JKwnHroGGqrKlj0UG6mhVVgxUAuvyE2k9nUD8gkiMIIsFwFVyrbCHNWjrC2mW4rSyQs1YPKOXlWPX9etp3tTa1Zb0+BVYQyvRarLzkNmxyGVy4nnE3eTtTnv3oz0EjDbKmVJWF56+yxdLlz2xMbs96WAksik6vwinKC3nxKd07FZNm0sjRqULIxdthg5k8awU8eXUfjvux+lwYMLDMrM7Pzs9qLpCSd0X65HBmYTTdhruQivKIOnLjtO4yLiXO5HSkeHzp2Cs1tnXz1rmVZbWfAwHL3BPC5rPYioesvwLIZKZjrgROp7jPOwRWmXLayeqOuQQnDhJHVvGvBBP7w3FbuX7494+2k2iX4FzP7FzObZGajDtwy3qtICuIUXHEJyFS6BnVBsYThnCPGM7Kmkt8+syXjbaQaWO8HLgMeApYGtyUZ71XSlu5Iwf4GXqTTBVg1YXZa+w1DLoKrmPT1ejKZGDddmiBXMlVRXsaUuiGseWVfxttIKbDcfVovt4Mz3qv0KarzWHFQqK2tuAViNq0sUEtLMjd++GDWNTbT0ZXI6PkpjxI0s3lmdr6ZffjALaM9SmiyOY9VCAMvUpGLEYXFINetrLBCS60sSTZ3wnD2d3RxzwvbMnp+SoFlZlcD1wW3U4D/Bs7JaI+Ssai6BQtNIYVWXAMwlQEYoK8hkdyaP2kE44YP5scPrcU9/S94TLWF9V7gNGCbu18MHAHk9upUeVU23YKl0k1YKNduZSusaawykW6wqGtQ0lVmxtvnHcTzm/ewbEtT+s9Pcb39wfD2TjMbBrwCTEp7b5K1bKZp6tkt2LOV1VerqxAGXvSmEA7yuZLJe5xtt2BvrSx1DUrY5ozrbuuszmDwRaqBtcTMRgA/pnuE4FPAY2nvTULRX6sq19M0FZpC6h7MRNWE2QX7gSCZBmFIrtTVDgJg8+79aT831VGCn3T33e5+PXA6cFHQNSghCev7sYqtlQXxD61s5KuV1d/yVKmVJQBVFWVUlhu7mtvTfm6/gWVmR/a8AaOAiuC+RCCXgy+KRSmHViFQK0tS1bivnY4uZ1r9kLSfO1AL69vB7fvAYmAR3d2Ci4NlUiDSGXxRjK0sKK5zWmEJs5WVSmiplSUv72wB4NCDhqX93H4Dy91PcfdTgK3Ake6+0N2PAhYAm/t7bjCN0wNm9qKZLTOzTwfL3xf8P2FmC3s85yozW21mK83sjLRfTZHpL3TCbmWVYmhl0soqhMsD0ukWFIlaU2sHAGOGpn/aI9VBF7Pc/fkD/3H3F4CBjlydwJXuPgc4DrjMzOYALwDvpnuap1cFj10AzAXOBH5gZuUp1ifktpUlqSvW906tLAnDyJruQReZfKFjqoH1nJndYGYnB7cfA8/19wR33+ruTwX39wLLgQnuvtzde/vody5wm7u3ufs6YDVwTOovpTjl8roqtbJSeG6RtUqyGXwhEoa6Id2BtWVPeIF1MbAM+HRwezFYlhIzm0p3N+LiflabACR/JeWmYFnPbV1iZkvMbElDQ0OqJRSlbK7JgtRaWXENrXyLupUVVtCqlRW95GPezh2NUZeTtfU7mgEYN3xw2s9NdVh7q7v/r7u/K7j9r7unFI9mVgvcAVzh7ulf2vzGWhYF59IW1tfXZ7u5ojNQt2DPVlaxhlYUAzCiDq10qJUVH8nHvFF1o6MuJ2sPvtTApJHVLJwyMu3nDjSs/fbg3+fN7Lmet4E2bmaVdIfVLe5+5wCrb+b1s2dMZICBHaUil4MvJFyFGFrZtr7UypJc2d3SzrItTbz3qEmYWdrPH6iF9eng37OBd/Zy65N1V3MjsNzdr0mhlruAC8ysysymATOAJ1J4nvSgVla0ogqtdINJrSzJt53BxcJzxqc/pB0GHta+Nfh3Q2+3AbZ9AnAhcKqZPRPczjKzd5nZJuB44I9m9qdgH8uA2+k+P3YvcJm7d2X0qopQMU5qG+YAh6iDtNBaWsU2mETiqbm9+5A+vLoyo+cP1CW418yaerntNbN+z0e5+yPubu5+uLvPD253u/tv3H2iu1e5+1h3PyPpOV9390PcfZa735PRKypBvXULxqWVVcwH0qrxswouuHrShcSSTy1tnQAMq67I6PkDtbCGuvuwXm5D3T2zNp1IiclnaPX3AaCYPxxIPLQELayhg0NoYUlhSXfwRbqtrJ7CbmWF1QLJpsUXVrgUcksr21aWSKr2d3QHVm1VCC0sKS09uwXjKOpzV/3JV2jlu5WlWdwlVbtb2qkoMwVWqUh38EW2raw4yTas8hEohdDSCuOrR/qiWdwl2aZd+zm4fgjlZekPaQcFVlHJxTVZcZ1jsJBbVj3F5T0VybXNu/czc+zQjJ+vwCpB2bayCu2arFzsN98hEvb+Bur6y3UrS916korOhDO4MvM5zRVYMZTt4IuBxLWVlamoXl8hvq+9hVa2NLxdDqgbMoitu/dn/HwFVkzpXFa3OHUF9ibKa7VSHYChVpbkypCqCrZm8LUiByiwilA+zmUVWrdgpgqllVModUA4rSyRzbv389ym3ZxwSOYT+CqwYizf12WlKl+hFYdRgeko5Jkxsm1lqVtQbn3iZaoHlfPpt87IeBsKrBKXzbcSF+rBNe5yEVzZPl+tLMml1a/sY+mGXXzy5OmMrs28B0iBFXO5HoAx0ByDPcW1azAOYXsguMKsNZ0LifNxLkutrOJ09/NbGTq4goveNDWr7SiwikA+uwbTOXhWTZhdkMEVh7DqKZ3gSutnlMf3QhcRl6aGvW0sXreD/3fM5IxnuDhAgVUkch1aybLtGizU4Iqj5FZX8vuej9YYaI5BSd9flm/HsKxbV6DAkj7kqmvwdevkMLgy3U4cW1f9KdSBGhp8IQAdXQn+tvIV3jpnDONHVGe9PQVWEYm6azDlLqsguDIOHbXW8kIDLyRbj6/dQVNrJx86bkpOtqfAKjJhhlY2X/LYl+TwSiWICimsenbPFWJLJ67Uyoq/1o4ufvnkRmYfNDSra6+SZXcGTArSrNFVff7Bz66vekO3TM/1+3v+sHFTX/fJu2r8rDeMNOttWarCDKRcBMqA5+tysI9C/6LFda/seUPre2Vj2xs+7PS2DLq7BXNxcbsUtjue2sSO5nYWffgoyjKcnb0ntbBkQAOdz8pFS6vQ5bMFla8WW7H9jKRwbG9q5e7nt3LB0ZM4asqonG1XgVWkCvnbieMk6q6+KPdfDF/oKdFYsn4XCYdPnTo9p9tVYJWoVLpk0hnqDn2HViEEVyY1FELdBxTK+yiSiqc37mLGmFomjqzJ6XYVWEUs2xnde0p3qHuyOB1sCzkcclVXob4+ib91jc2s2LaX02aPzfm2FVglLBddg+l8d1YcvncqDgfyqAM1rl9FI+Hb19bJd/7yEvW1VXzixGk5374Cq8il28rKhYFCK58H23SmM4pDWCXLtOa4vU6JB3fn+gfXsLO5nR986Ejqspjkti8KLBlQuq0sSG34d6GMgov7ATzV9zKd91wDLiRd97ywjaUbdvGld8zmyMkjQ9mHrsMqAdlel9WbaWOGv25euZ7XZ0Fq12MlH0Bzdf1RsXUBpqqYXgv0fR2XFJ51jc3c+sTLnD5nLB/JwZyBfQktsMxsEnAzMBZwYJG7X2tmo4BfAlOB9cD57r7LzE4GfgesCzZxp7v/e1j1SXpSCbG+QgtSC6PeDriZPi8VYR3gc9E6iXJapP7q7+v8lYKldLV2dPG9v66irnYQ//2ewzHLzUXCvQmzhdUJXOnuT5nZUGCpmd0HfAS4392/aWZfAL4AfD54zsPufnaINUmKMmllQe+hBZnPfhFWqORyu2F0n/Xcpub1k0L107+vZ+ueVn7xieMYOWRQqPsK7RyWu29196eC+3uB5cAE4FzgZ8FqPwPOC6sGeU26FxKnuo3ePnH3dQAvhIENuaxh2LipeTvXk6996dyVpOPR1Y08+FID/3TqdI4/pC70/eVl0IWZTQUWAIuBse6+NXhoG91dhgccb2bPmtk9Zja3j21dYmZLzGxJQ0NDmGVLFvo78EURWrkKqgPBEdWBPcx9D7RddQdGI/mYt3NHY9TlvGr1K/u48ZF1HDVlJJefNiMv+ww9sMysFrgDuMLdm5Ifc3en+/wWwFPAFHc/ArgO+G1v23P3Re6+0N0X1tfXh1i59HYgSrWVBQOHVr5GCma7j6hDqje5rCeVbWVy7ZWCLDeSj3mj6nIz63m2nt+8h6/f/SKjawdx3QcWUFGenwHnoY4SNLNKusPqFne/M1i83czGuftWMxsHvAKQHGbufreZ/cDMRrt74XykiLl0Rwums53ezmfBa6HV3zmYXI4UzGV3Xxwk15nJea5sX6dCqfQ8sW4n1/11FQfXD+H/PnYsY4YNztu+wxwlaMCNwHJ3vybpobuAi4BvBv/+Llj/IGC7u7uZHUN3629HWPVJavoKuXRCC/oejNFT1Oe44hJUvUk1vNJ9jZrZQg54cWsT197/EkdMHMFNFx/NiJpwB1n0FGYL6wTgQuB5M3smWPZFuoPqdjP7GLABOD947L3AP5pZJ7AfuCDoMpQ86auVlW5oARm3tqIQZkj1d7DvK9xzIVevqb/6+2tdqeVVfPbs7+B7f13FlLoh/Pzjx1Jblf/LeEPbo7s/AvQ1IP+0Xtb/HvC9sOqRbqkMV8+FgVpbEH1whRFU6bRGels3zBBLl1pWckDCnR/8bTXNbV3c8vEjIwkr0NRM0kNfQ9z7+sTc3yfpgQ54UQ1kCGO/08YMz8kB/sB2og6LgfafTetK3zYcP79aspHnNu3h6nPmMGf8sMjq0NRMJWigVlYmXYNAr4/119I6IB8trrCCMcxg6bntfLW+sgkrKT6Prm7kt89s4QPHTOb/HTM50loUWJKW/sKur8f6O6+VLNezO0R1biof+wwrvLJ9XQqz4rKmYR8/emgNx0wdxb+dMzfUaZdSocAqUZm2sgZ6bn+PpdLaSlZoI/ai7qZLluvWV6qvLdtAUndgfOxv7+K6v66ivraK6y88ikEV0Z9BUmBJn8IKLSiswQV9KaSAGkimAZbOaxworHLdulJrLVo3PbqOhr1t3P4PxzMq5DkCU6XAKmHZjhjMNLQg/dZWvsQppPpTLK9DovHo6kYeXt3IFW+dwcKpo6Iu51UKLOnXQDNgZBtaEH1rKx8H91RbC/m45CATuWhdqTswHrbtaX11jsBPnTI96nJeR4FV4lJpZaUzbVMm248quMIOqky6tHp7TtQhpq650tHZleB7D6xiUEUZ383jHIGpUmBJ1qE10PNT7XoM+0LaQmpJZbvNfIRYqq9FgVYc2jsT/OBvq1nT0MyPLjyKCSOqoy7pDRRYkhO5Cq2e4nAuJooDds995jrAch1W6XYHKgTza19rJ9++byUrtu3ly++YzRlzD4q6pF4psATITddgKqEF0XdxZasQD6a5CLB0X1dYYSX51bivjW/eu4JXmlr57gcWcM4R46MuqU8KLHlVPkIr1XUKSSEG1EDiWLPk3459bXztDy+yv6OLmz96bF6+NTgbCixJWyqhBf1/yi/k1pYO9v1L5/3JpHWl9z8/dre08/W7l9PS3sUvPnEsh08cEXVJA1Jgyeuk2vpJZeRgqq2tZFEEWCGcgxpIoQR72GEl+bG3tYP/vGc5u1s6+PnHjolFWIECS3qR79DquX4xydXriXq4e7qvI9OwKraffyFqbuvkG/es4JWmNm76yNEFdWHwQBRY0qt0QgvIuouwWOTzgJuvEMtXWEn49rd38V/3rmDjzhZ+fNFC3jR9dNQlpUWBJX1Kp3WUamsLiiu4Cq1F0Fc96b7nmb6ubMKq0N7LYtPemeBbf17B2oZmvv/BIzll1pioS0qbAkv6levQOrBNiF9wxfmAmo/a1bIqXF0J57q/rmLF1r1854L5nDmvMK+zGogCSwaUbmhB/12EyduFwg6uOIdUPmUbVnqfw+Pu3PDwWpZs2MW/nTOXc+dPiLqkjCmwJCXpDp7IJLgg911XpTzgIx9y0arS+x6uu57dwt9eauDy02Zw0ZumRl1OVhRYkrJMLvhNJ7gO7COX4nYwTA6ATCcczheFVeFb07CPXy3dxFmHHcQ/v3VG1OVkTYElacl0lopsZnwvBpkc3FN5TlTvqcKq8LV2dPG9v65mzNAqvvGuwyP/evtcUGBJ2jI995RuayuO8j3woLf9hfn+Kqji46ZH17G9qZXbLjmO4TWVUZeTEwosyVg2rS0ojuAqxJFxfdWU6fudy9eosMqPh1c18NCqRi4/bQbHHlzY8wOmQ4ElWclmpF+cztckK8SQSkXUdSus8mPbnlZuenQdR08dyeWnFtY3BmcrtMAys0nAzcBYwIFF7n6tmY0CfglMBdYD57v7LuvuYL0WOAtoAT7i7k+FVZ/kVrZD1HseTAspwKI+0Medgip/3J2fPLqOivIyrr2g8L4xOFthtrA6gSvd/SkzGwosNbP7gI8A97v7N83sC8AXgM8DbwdmBLdjgR8G/0qM5OqrQ8IKib6CUKEUDoVVfi1Zv4vnN+/h6nfOYXwBfmNwtkILLHffCmwN7u81s+XABOBc4ORgtZ8Bf6M7sM4FbnZ3Bx43sxFmNi7YjsRIIV8QrGDKH4VVfrV3Jvj54g3MHFvLhcdNibqcUOSlvWhmU4EFwGJgbFIIbaO7yxC6w2xj0tM2BcskpmaNrtJBq0Tp555/97ywlYa9bXz1nLlF1xV4QOivysxqgTuAK9y9KfmxoDXlaW7vEjNbYmZLGhoacliphEXBVVr0s86t5GPezh2Nva7TtL+Du57dwmmzx/CmQ+I1A3s6Qg0sM6ukO6xucfc7g8XbzWxc8Pg44JVg+WZgUtLTJwbLXsfdF7n7QndfWF9fH17xknMKruKnn2/uJR/zRtX1HkZ3Pr2Zto4EV7390DxXl1+hBVYw6u9GYLm7X5P00F3ARcH9i4DfJS3/sHU7Dtij81fFScFVfPQzjc72plbuX76d84+exPQxQ6MuJ1RhjhI8AbgQeN7MngmWfRH4JnC7mX0M2ACcHzx2N91D2lfTPaz94hBrkwKQzaS3hS5XB+9Cfl8UUIXhV0s2UlFmXFEEcwUOJMxRgo8AfU1edVov6ztwWVj1SGHrefAr5AP1Afk4YKezjzDfM4VTYdre1Mqja3bwjycfwthhg6MuJ3Sa6UIKUr6+/j1VcThgx6FGya2/rXyFMoOLjp8adSl5ocCS2Ej1gJyvr4MXiVJXwnloVSMnz6znoOHF37oCBZYUIQWQlILlW5vY2dzO+xZOGnjlIlGcV5eJiBS5J9fvZHBFGSfPGhN1KXmjwBIRiRl3Z+mGXbxlZj3Vg8qjLidvFFgiIjGzZU8rO5rbOeXQ0mldgQJLRCR2VmzrnuXu2GmjIq4kvxRYIiIxs3LrXuqGDGLa6CFRl5JXCiwRkZhZ3bCPo6aMpHsGvNKhwBIRiZF9rZ1s3dPKEZNGRF1K3imwRERiZG3jPgCOmKjAEhGRAra2oRmAwyYOj7iS/FNgiYjEyNrGfUypq2F4dWXUpeSdAktEJEY27mxh7vhhUZcRCQWWiEhMONCwr52pdaU1nP0ABZaISEx0diXoSjhT6mqiLiUSCiwRkZjoTDgA40dUR1xJNBRYIiIx0RUE1qghgyKuJBoKLBGRmOhUYImISBwkgsAaNrj0hrSDAktEJDYS7hhQU0LfgZVMgSUiEhMJh5qq8pKb9PYABZaISEwk3BlaVZrdgaDAEhGJjUTCGTq4IuoyIqPAEhGJiS53hpXgHIIHKLBERGKiK+GMrFFg5ZyZ/cTMXjGzF5KWHWFmj5nZ82b2ezMbFiyfamb7zeyZ4HZ9WHWJiMRVV8IZUVOa12BBuC2snwJn9lh2A/AFdz8M+A3w2aTH1rj7/OB2aYh1iYjEUsJL9xosCDGw3P0hYGePxTOBh4L79wHvCWv/IiLFJuFObVVpXoMF+T+HtQw4N7j/PmBS0mPTzOxpM3vQzE7Mc10iIrFQU6VRgvnyUeCTZrYUGAq0B8u3ApPdfQHwGeAXB85v9WRml5jZEjNb0tDQkJeiRUSiknzMAxhcUbpj5fL6yt19hbu/zd2PAm4F1gTL29x9R3B/abB8Zh/bWOTuC919YX19fb5KFxGJRPIxD6CiXIGVF2Y2Jvi3DPgycH3w/3ozKw/uHwzMANbmszYRkTioLC/NaZkAQusMNbNbgZOB0Wa2CbgaqDWzy4JV7gRuCu6/Bfh3M+sAEsCl7t5zwIaISMkrK9F5BCHEwHL3D/Tx0LW9rHsHcEdYtYiIFIvystINrNLtDBURiaESbmApsERE4qSUuwQVWCIiMaLAEhGRWFBgiYhILJTwZVgKLBGRODG1sEREJA7KFVgiIhIHZSV81C7hly4iEj+GWlgiIhIDZZrpQkRE4qCE80qBJSISJ+oSFBGRWFALS0RE4kGBJSIicaAuQRERiYUSvm5YgSUiEiclnFcKLBGRONFcgiIiIgVOgSUiIrGgwBIRiYnxwwczpa4m6jIio8ASEYmJutoqxg4bHHUZkVFgiYhILCiwREQkFhRYIiISCxVRFxCFupryqEsQEZE0hdbCMrOfmNkrZvZC0rIjzOwxM3vezH5vZsOSHrvKzFab2UozOyOsukREJJ7C7BL8KXBmj2U3AF9w98OA3wCfBTCzOcAFwNzgOT8wMzWDRETkVaEFlrs/BOzssXgm8FBw/z7gPcH9c4Hb3L3N3dcBq4FjwqpNRETiJ9+DLpbRHU4A7wMmBfcnABuT1tsULHsDM7vEzJaY2ZKGhobQChURKQQ65r0m34H1UeCTZrYUGAq0p7sBd1/k7gvdfWF9fX3OCxQRKSQ65r0mr6ME3X0F8DYAM5sJvCN4aDOvtbYAJgbLREREgDy3sMxsTPBvGfBl4PrgobuAC8ysysymATOAJ/JZm4iIFLbQWlhmditwMjDazDYBVwO1ZnZZsMqdwE0A7r7MzG4HXgQ6gcvcvSus2kREJH5CCyx3/0AfD13bx/pfB74eVj0iIhJvmppJRERiQYElIiKxoMASEZFYUGCJiEgsmLtHXUPGzKwB2BDS5kcDjSFtO9dUa+7FpU5QrWHJZ62N7t5z7tU3MLN7U1mvWMU6sMJkZkvcfWHUdaRCteZeXOoE1RqWONVaKtQlKCIisaDAEhGRWFBg9W1R1AWkQbXmXlzqBNUaljjVWhJ0DktERGJBLSwREYkFBZaIiMRCSQaWmU0yswfM7EUzW2Zmnw6Wzzezx83smeAbPo8JlpuZfdfMVpvZc2Z2ZAHUeoSZPWZmz5vZ781sWNJzrgpqXWlmZ+Sx1sFm9oSZPRvU+m/B8mlmtjio6ZdmNihYXhX8f3Xw+NQCqPVTQT1uZqOT1o/yd6CvWm8JfsYvmNlPzKyygGu9MVj2nJn92sxqg+WR/A70VWfS4981s31J/4/sd1WSuHvJ3YBxwJHB/aHAS8Ac4M/A24PlZwF/S7p/D2DAccDiAqj1SeCkYPlHga8F9+cAzwJVwDRgDVCep1oNqA3uVwKLg/frduCCYPn1wD8G9z8JXB/cvwD4ZR7f175qXQBMBdYDo5PWj/J3oK9azwoeM+DWpPe1EGsdlrTONcAXovwd6KvO4P8LgZ8D+5LWj+x3VbfXbiXZwnL3re7+VHB/L7AcmAA4cKClMhzYEtw/F7jZuz0OjDCzcRHXOhN4KFjtPuA9SbXe5u5t7r4OWA0ck6da3d0PfCqtDG4OnAr8Olj+M+C8pFp/Ftz/NXCamVmUtbr70+6+vpenRPk70FetdwePOd1feDqxgGttgu7WH1BN9+/FgVrz/jvQV51mVg58C/hcj6dE9rsqrynJwEoWNO0X0P0J6wrgW2a2Efgf4KpgtQnAxqSnbQqW5VWPWpfR/UcE8D5gUnA/0lrNrNzMngFeoTtI1wC73b2zl3perTV4fA9QF1Wt7r64n9UL6n1NrjXoCrwQuLeQazWzm4BtwKHAdT1rzffvQB91fgq4y9239lg90t9V6VbSgRX0o98BXBF8AvxH4J/dfRLwz8CNUdaXrJdaPwp80syW0t1V2B5lfQe4e5e7z6f70/4xdB+cClLPWs1sXtQ19WWAWn8APOTuD0dT3ev1Vau7XwyMp7uX4P0Rlgj0Wudb6P7wd13/z5SolGxgBZ9K7wBucfc7g8UXAQfu/4rXutI281oLBrp/wUbXcw4AAAJaSURBVDfno07ovVZ3X+Hub3P3o+g+f7GmEGo9wN13Aw8Ax9PdJXXg262T63m11uDx4cCOPJeaXGt/k4oW2vt6JoCZXQ3UA59JWq0gaw2WdQG38VoXduS/A0l1ngJMB1ab2XqgxsxWF0qdUqKBFfQ93wgsd/drkh7aApwU3D8VWBXcvwv4cDD66jhgTy9dBnmt1czGBP+WAV+mezDDgVovCEY1TQNm0H1+Ix+11pvZiOB+NXA63Z+mHwDeG6x2EfC7pFovCu6/F/hrcD4mqlpX9POUKH8Heq3VzD4OnAF8wN0TBVzrSjObHiwz4Bxee68j+R3oo86l7n6Qu09196lAi7tPj7JO6SHbURtxvAFvpvuk73PAM8HtrGD5UrpH2S0GjgrWN+D7dLdingcWFkCtn6Z7xOBLwDcJZi0JnvOloNaVBKMe81Tr4cDTQa0vAF8Jlh9Md2iuprvlWhUsHxz8f3Xw+MEFUOvldJ/z6aT7A8wNBfA70FetnUE9B34vvlKItdL9wfjRoJYXgFsIRg1G9TvQ13vaY53kUYKR/a7q9tpNUzOJiEgslGSXoIiIxI8CS0REYkGBJSIisaDAEhGRWFBgiYhILCiwRHphZn+PugYReT0NaxdJkZlV+GtzIopInqmFJdKLA9+FZGYnm9nDZnYX8GLEZYmUtIqBVxEpeUcC87z761pEJCJqYYkM7AmFlUj0FFgiA2uOugARUWCJiEhMKLBERCQWNKxdRERiQS0sERGJBQWWiIjEggJLRERiQYElIiKxoMASEZFYUGCJiEgsKLBERCQW/j9jpYFZ6/+sBgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(d[\"ir\"], d[\"lidar\"], d, kind=\"kde\") #度数分布を描画\n",
    "d.cov()                                                                    #分散、共分散を計算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yKA11zeR8u59vVxewaslOFi/Ygp+/gayRaYy+qE+3aO5TOk4F+nNsx5YiXnluMYX7jjIgK4X/e+CS86KJxu5wsq3gCNsKSti25wj5B4/ibJvILDk2lL49Y7jswv6kJYbTMzGCyJCumffljitHcu0lQ2iytVBd10xokD8tDhfNdgdajSA0yJ8po/rw/ldbcLjczLnpIoID/AgO8GNcVk/ufuZj/EwGDDotd109ivSkCNKT/rvQzQWDevDnuSuYmJ1Bi8OF0+WmZ0I4TTYH5hN6udQ1NuN2e/6na+f3bc5r7eraKyWSIIvfD+7na4HB/oyf0p/xU/rjcLjYvrmQb1cXsOGbAtYuz8NsMTH24kwmTB1InwEJqk3/J0Z1rzxH6mubeOW5xXzz9S4io4O4/deTuWB873P6A6xrtLFu20HWbN3Pxp2HsDtcaLUaeqdEMTA9joEZcfRPjz2rAawzXC43ZdUN1DfaabY7yEyNwexnwO1pbdA/FrD/9eUmFq/LRyNgzs0TGJgRx9b8Yv715WbMfkaMBh3WZjtzbr6I8ODTX2Xd/sR8tu9tXVAtPiqYQRlxDMyIZ2BGHHGRQWf9/9ft9rBjSxHLvsxl3YrdtNidxMSHMmHqACZdOoiIqKCzWh7Ft1Q/+vPYhjV7eOHJhTTW27jmlgu4+qYLzlkf6eq6JpZu2MM3OfvYsbcUj5REhloYMziV0YNTGZAWh5/pp3fJb7M72X+kknqrnQarnYEZccRGnDko1ltt7CmqIL/wKDv3lbJ9bwkNTS0AhAebGZgRz9DMBLL7JRN9lpuBbM0trFuRz7Ivc9meU4hGq2HkuF7MuHoY/Yckq1r+j5AK9Ocht9vDWy8uZcG870hJi2LOE1fQI+3MNyN9Xg6Phw07ivh05Q6+3V6I2yPpmRDOmCGpjB3Sk4wk1V3PVzweSWFJNbl7Ssjde4RtBUeorG29J5AQHczgXgkM7hXP4N7xRIYGnLVylZfU8uUnm1ny2VYa620kpkQw6dJBTJg64Ly6N6Scngr055kWu5NnH/mE9SvzmXHNMG67b9JZ7xFR29DM59/s5LNVOymraiA0yJ9pozOZOjqT5NjQs1qWU7HaW6hustFgt1Nns1Pf9miwtdDicuFwu2lxuXG0PXd7JNpjyw0KgVbT+tyo0+JvMOCn1+Nv0OFvMOBv0BPsZyLE3+/4w6g/+7eopJQUltawcUcRObuLyd1bgrW5tcafGh9Gdv9kRvZPoX96LIazUL4Wu5Nvlu7iqwU55O88gk6nZfSEPlw2K5te/eK7/PhK56hAfx6pr23i0V9/QMHOI9z+60lcce2Is3v8Rhv/XpzDx8tysbU4yeqTwBXjBzBmSCr6DvaG6QiX28Phmjr2VVZTVF1LWX0jZfWNlNY3UFbfiLXlh5cb1AiBQavFqNNi0GnRa3XoNAKPlHgkeKSn9blH0uJy0+xw4D7Dd9vfoCfM7E9UoIWYwACigwLa/lpICAkiMSS4y08Gbo+HfYcr2Zx3mA07isjdU4LL7cHPqCerTwIXDOrB2CE9j4/o7UqHDlaw+JMcln6RS3NTC+mZccy4ehhjL+6rummep3wW6IUQCcC/gChAAm9IKV8UQlwFPAb0BoZJKXPa9k8G8oE9bVlskFLeebpjdOdAX13ZyO/uepfy0lrmPDGT0Rf1OWvHbmyy8/6SLXy4ZBu2FgcTszO45dJserSN9uxKdqeLHSXl5BaXsq+imn0V1RyoqsHp/u8ShMF+JmKDAokJOhZkLYRbzAT5mQjyMxHc9jfAZMTg5QlJSonT7abZ4aLZ4aDJ4aDeZqe22U5ts43aZhs1TTaqrE0cbbBSWt9IRaMVV9uNWmhdKDk2OJDksJC2RzAZURH0igon0O/Mo3k7otnuYMvuYr7bUcR3O4ooraxHqxEM7p3A+GHpjBvSk9Cgrg36zU0tLF+Uy8L5myguqiIoxMyMq4dy2exsLAE/jhvxPxW+DPQxQIyUcqsQIgDYAlxGa9D3AK8Dv/leoP9SStm3vYXtroG+qqKB3945l6qKRp548Tr6D0k+K8e12Z28v2QL73+1BWtzC+OHpvHzy0ccH3DUFeqa7Ww9XMKWwyXkHC5ld+lRnG1BMzYogLTIcHpGhJIWGU5aZBgp4aH4G86vm7xuj4cqazPlDY0crqmnqLr2hEcdTY7/XnHEBQfSKyqCXtERZMZEMiA+hjCLbwOwlJJ9h6tYuWkvKzbt5XB5LRohGNQrnsmjenPRsPSTuoD6mpSSrRsP8vmHG9i4di9mi4nLr83m8mtVwD9fdFnTjRDic+BlKeWytn9/gwr0/6OivJ45d8ylvraJJ1+6nsyBiWfluCs37+X5f39DRY2VMYNTue2KEcfncfG1g1U1LMvfz+q9heQeKcMjJXqtlv5xUQxOjGNIYiwD42MJ9u+a2u/ZJKWkorGJvUeryC+voKC8koKjVRRW1XDsF5QUGszAhBgGxccwMCGWtMiw0/a59/b4B45UsWLTXpZvaA36JoOO8cPSmTq6D4N7JfzgNMy+cGBPGfPeXM36Vfn4m41cNrs14Ad28dWFcnpdEujbgvgaoK+UsqFt2zf8b6DPA/YCDcDDUsq1p8jrduB2gMTExCGHDh1qdznOd26Xm1/d+jbFRVU8/Y8b6N0vocuP6XC6eGHeaj5ZsZ20xAh+c+N4BmbE+fw4RxusLNyRz+Jde8gvrwQgMyaScek9GNEjgX6x0efkJue5YnM4yS+vYFtxGRsPF7OuoRCHzY22QUuA3khWUhzDkhMYlhxP7+gInwR+KSW79pfx5do8lm3YQ5PNQWSohUtG9WHG2L7ER3XdlBkH9pYz781vWL+yLeDPGs7MG0aqGv454vNAL4SwAKuBp6SUC07Y/g0nB3ojYJFSVgshhgCfAZnHTgyn0t1q9PPnruWdvy/nwaevZNykfl1+vKM1jTz40hfkHSjn+ilZ3HX1Bei0vp3YaseRct7dsJWvd+/D5fEwID6GqX3TmdQnnahA1R1PSslRm5UtFUdYfmg/m44W01cXw+GSegqrW5dztBgNZCXFcUFqMuPSU4gP6fxgJbvDyZotB/hqfT4bdhThkZJhfZO4fHw/xgxK7fDUE2dycF8577+5mrUrdmMJ9OOqG0Zy2exsNWf+WebTQC+E0ANfAl9LKf/2vde+4YRAf4q0p30dulegLzpQwS+ue43hYzJ4+Nmru7w/es7uwzz88iJanC4euX0S44f6boZFl9vD8oL9zP1uK7lHyrAYDVw5uC/XDh1AYujZmWjN7fFQaW+i2t5MXYuN2hMeTU4HDo8bp9uN09P6cHg8aGjtoaPXaDFoNBi0OgxaLYF6E0FGE8GGtr9GP0KNfoSbzD5rYjnm7zvWY3U6eHDIhVQ0WtlcVMKmomI2FBZzqKYOgJ4RoYxNS2Fseg8GJcSg13YuKFfUNLJw9S4Wrt7F0epGwoLMTB+byeUX9u+ywVn7C8p499WVbFq3l+BQM7NuGc3UmVlqXp2zxJc3YwXwLlAjpbzvFK9/w8k1+oi2fd1CiB7AWqCflLLmh47RXQK9y+nmvlveoqKsjjc+vrvLB54sXrebJ99aSkJUMM/eO8NnfeHdHg8LtuXx6pqNlNY3khgSxPXDB3HFoEwsxq6psVXYrOyqLudgQw2HG+s41FhHsbWOI9Z6HB73KdOY2gK4XnPsoUGv0eKRsi3oHzsJeGhxu3BJzynz0QkNUf4WYvwDiTYHEOsfQGJACD2CQukZGEaEn7ndJ2ynx41eo+U36xfRNzSKm3uf/BustjeTd/QohaW1rN5XyOaiIzg9HoJMRi7uk8aUvhkMS47v1InH7fHw3fb/DogTGsGkEb24YWoWPeK75ob87h3FvPvKCnI3FxIZHcRt901i9IQ+auBdF/NloL+A1mC9k9ZeNgAPAUbg70AEUAfkSiknCSFmAn8EnG37Pyql/OJ0x+gugf6Dd9Yw9x8rePjZqxk9IbNLjzVvcQ4vfbCGrD4JPHvfDCx+nV9YWkrJ2v1FPLdsLfsqqhkQF80do4cxNj3FpzXeBoedrZWl7KwuY0d1OTuryylvbjz+eoDeSFJAMIkBwSRaQoi3BBFu8ifE5EeI0Y9gox/BBj8MXtSApZTYXE7qHHbqWmzUO+zUt9iptDdR3txIWVMDpU2NlDU3UNbUeNLJ5cupN9M37IdHMHukRNMW0IqtdSwqKuCzg3m8Pf5K4iz/bZ7Jr63g1Z0bOGStpdnp5O9jZhDvH8y3Bw6xLH8/K/YcoNnhJNzsz+TMdKb0zWBQQueWhyyvauCDJVv5bNUO7A4XowenctO0ofRLi+1wnqeTu+kgb76wlP17ylon6ZszheTUrukMoKgBU2ddaXENt1/1MtljMnj4z9d06bHe+WwDr3/yLRcNS+exOyf7ZARlZWMTD372NesOHCIxJIhfT7iASX3SfFYjK21qYPGhAr46tIdtVaXH56vvERhK/7AY+oZF0S8smozgCIIMpnNaE/RISXlzIwfqqznYUMPVPfvjp/vfpohd9QewuprJDutHvcPOS9vXs6umnGGRCcxI6UNacPjxGn5BbQXvFmwl3hLI3f1GMjc/Bw+SW3sPPZ6fzeFk9b5CFu/awzd7C3G43SSEBDFzUF8uH9inU/dC6httfLwsl/nLttFgtTMoI47bZo5kSG/fdxRwuz0sXpDD3Fdap92+bNZwbrjjQvzNna+MKCdTgf4se+fvy/j4vW/596JfERbRdZNV7dhbyu1PfsikEb34wx2TfVLT3nq4hHs/WkSjvYVfTxjFrKwBXg9QOpV6h50FB3bxZVE+WypbZ3TsGxrFhXGpjIhOpG9YNIGGH2fXy2aXjQ3Vu1hS9i1HmmuoqQthSvxQbsoYQpDxv+/pWG3/2a3fYNTquDZtIJH+Fj7Ym8vXxXuZe9HVx1ezOnby0wiB1d7C8oIDfJq7m41FxWiFYGx6ClcO7suYnikdvtnebHfw+aqdzPsqh8raJoZmJnLHzJFdUsOvr21i7isr+OrTrYSGW7h7zlRGje/t8+P8lKlAfxZ5PB5umv4CiT0ieOrvN3TZcewtTq5/+D1cLg/znr7RJ4Nllu7ex/2ffEVsUAAvXT2NjOiIMyc6g9KmBt7J38wHe7fT5HLQOySSacm9mJrUm+TAkE7nfz7xSMlTuZ+zpjKHZH1/rk0fwoVxqSftU++w8+t1X3BHZjZZkfFohODu1Z8xIjqJ6zMGUWu34afTYTrFVQPAoeo6/rNtF5/l5lFpbSYywMzsrAHMGtqfEP+OdWtscbj4dNUO5i7cRG1DM6MGpnD7zJH0Svb9WggFO4/w0jNfcGBPOeMm9ePuOVMIDFb9732hvYH+p9PhuQvlbS+moryem+++qEuP89p/1lNcXsfLv7vSJ0F+wbY8Hl64jP5x0bx+3WUEdXJYf35tBW/mbWRhYT4SybTk3tzWZ9hp27d/zJweJ3qNnilJGTSIIsYGZ/LO7s3UtdhIDQwjKSCEIKOJfXVVxPgHEuFnRiMERQ212FxOBkfEUlBbwdeH9/Jt+SHCTWYeGDT2f06GSWHB3D/hAu65cARr9hXxwebtvLjqW15fu4krBmVyU/ZgksK86wVlNOiYNWkwl47tx8fLt/Hel5u56ZF5XDg0jV/OGk1cpO96VfXqF89L797O/LlrmffmanbkFHLvwzPIHpPhs2Mop6dq9D7w4tNfsGLRduYvewA//65ph9y25wh3PfURV4wfwJybO39Cefe7rTzz9WpGpSbx92umd2o6gv311Tyds5KVJQfw1+mZlTaAW3sPJd7SdYtauKWHOkcjDU4rDc4mGlxW6p1NNDitODzOtsnOPHjwtE1uJjFqDPhpjZi0Rvy1Rvy0Jsw6P8KMQYQZgrDo/M94b+BYM8sxzS4bf8x7k5HhA7g4egQmrQGby8mGo4dYX7WNnsGBjAobxiMbl/HS6BkEGkw8vnk5AXojo2KS+PeebZi0Op4bNZWP9m2nsLGW3w4ed8pjlzY1oBMaIv0t7KuoYu53W1m4owCX281FvVK5deQQBid2bJCctbmFD5ZsYd7iLbg9Hq6bksVN04b5fC2CA3vKeO7RTyncd5SJ0wZy528mq8FWnaCabs4Sp9PF7El/YUh2Tx58+srV2IE8AAAgAElEQVQuOUaLw8X1v38Pl9vDvKdvwN/U8dq8lJK/f/Mdr6zeyMW9e/KXmZdg0HXswq7BYeelHeuZm78FP52eOzKHc33GIIKNvvvheqSHoqYyDjeXc6T5KEdsRznSfJQSWyUOj/OUaXRCi1ZoEAg0QoNGaBBAi8f5g2kAbkmZwZUJE9pVrk3VeeTU5HHEVkGKOZbbUq846fUyWyVvHPiUypbWwVKVDUZGhA6hT0gUT21ZybyJs1lyeA/766o50FBNkMGEQavFpNXxVPZkjFrd8Z48Ukq2VpXy6s7vKLbWE27y58XRMwj3M1PZ2MT7m7fz/ubt1NvsDE9O4O5x2QxL7tgUw5W1Vl6ev5Yl6/OJDLVwz+yxTBie7tOb406ni/ffXM2Hc9cRGmbh149expDs1DMnVP6HCvRnyfacQubcMZfH/jabEWN7dckxFqzcwbP/XM6Lc64gu19yp/JauD2fOZ8uYeagTB6fNqHDN/UqbFauW/oh++uruKbnAH4zaAzhfuZOle0Yt/SQ31DI+spc1lflUu2oB0CDIMoURrx/FPH+UUSbwgjWWwjUWwjSWwjUmwnQmdFpfvhGssvjxu5pweZqwea20+hqpsZRT1VLPX2DUkkLOP2cRJuq81hUupZgQwADg9PpFZhMjF/E8XJrhQaXx83Kik3sazzM3WnXcNRezVclm8gpsRJuCmZKUi+GRSXwz/wcKmxWfjt4HDuqyvi8cDehJj9uzxyOXqPF4XZj0GpZdeQAy47so09IFNdnDOLpnJUMi0pgQkIaTU4HNpcTf62Bj7fs5K31m6m0NjM2LYXfTLyAtMiO9ZvfvreEv/5rFXsOVTCifzK/u2WCzwdd7ckr4S+Pfsrhwkquu20s198+Do2PB651d6qN/iypqbICEJfYdVP/fre9kNiIIIb3TepUPi1OFy+sXE+fmEiemD6xw5NglTc3cu3SDyhvbmTexFmMjEnuVLmgtda6u+Eg31Rs4duq7dQ5G9ELHUNCe3NjWH96BiQQ6xeBQdO5pgSdRotF449F5/3NQI/0sN96mNy6PUyKHsG4yKyTarpa0RqkrK5mvqvaQWVLLQ3OJqJMYdycegk3p56cV3JgCJsrigHoHx5D//AYrM4WVhzZT4/AUNKDW08gXxTtZmhkApMTW9u07W4XmyuOMCEhjbyao/z228X0CY3i2vSBLMv6GfM25fLamk1c+uq/mTkok3suHElEgHcn4QHpcfzzj9eyYMV2/jF/Hdc+9C9+c+N4Lhnlu3WNMzLj+Pt7t/PynxYx783V7NtdypwnZxIQqJpyfE2dPjupsaEZgMCgrvlyulxucnYXM7xfUqd/YPM2b6e0vpEHJo7ucJAvsdZzzdfzqLBZ+deEazod5KWUbKvdw2+3v8Sc7S+y4ugm+gal8rveN/PByGd4JPM2JkQPJ9kc2+kg31kaoeHapEuYO/xxDFoDt21+gk3VeTi/1xwUbAjgVxnXMyZiME/vfpsyW9Xx1zxto3M1QsPQyHgi/SxMWvg2t636hO1VZQgEVqeDW1Z8zOu7NpJfW0GDo4WsyHhCTK3fsYLaiuM9e4ZFJbBkxs+4OCGNd/I3U2pr4Gejslh67y1cP2wgn+bu5pKX5zJvU+7xRdHbS6vRcNXEQbz/9I30TIjg8deX8PA/FlFvtXXmYzyJyc/A/Y9dxi9+N5WtGw/yy+tf58Decp/lr7RSNfpOaqhr/dJ31Q2lvIPlNNsdDOvbuWmOmx1O3lq3mZE9EhnRo2N51Tvs3LjiI2rsNt6bMItBER3vey2lZEttPh8cXkJBQxHhhmDu6nklE6KyMWnP74mxQgyB/LzHZVyTcDE1jnqWl28i1BjI8LB+ODxODBo9gXozVydeTKOrmY3VO7ks/kLqHY18W7WD7fV7GRaayfioYTw2bCLNTgdfHd5DlL8Fs97Alan9uDK1dRDWt2VFpAWHE9Q23mBNaSFhJjNJAa29YhodLQQYjFzaI5MXd6ynvKmBHoGhhPj78dAl45g9dABPLF7JE4tX8Wnubh6fdhGZsd51oYyNDOLV31/Fe1/m8MaCb9m+t5Q/3D6JYZ28wjxGCMH0q4aRmhHDk3Pm86ub3+Leh6dz0ZQBPslfUTX6TmtssOFvNqLTd80sgRt3HkIjBFl9OhfoP9i8nZpmG78Y17FlDJ0eN3ev/ozDjbW8eeHMTgX57XV7+XXuX3l012tUt9Tzi57X8NawR5gWO+a8D/InCtD7k2SOYUL0MOL9onB6XCwr30BJc8XxffIbCgkxBFLraOCNg59ysOkIt/W4gs01u/ng0BIA/PUGZqb2I9q/dXHwY6tcBRlMRPkHcKC+mkj/1lGx8/ZuY2hU/PH7IcuK9zF4/os8sH4RIUY/BkeefBM2JTyEt2+4gr/OnEJ5fSNXvfkBT321Cqu9xav3qtVouHnGMN55bDZmPwO/fPYTnv/3N7Q4XB378E6hT/8EXv73HaRnxvLnRxbw1ktLcbu9uwpRTk3V6Dupsb6ZgC5qtgHYuOsQvXtEEWjueB93u9PFO99uYWSPRAYndixAP7l5BevKinhu5BSyozt20vFID6/u/w+Ly9YRZQzlnrRZjI8ahl7z4/4a6jV64vwjkVKiERqe3P0WyeZYokyh1DusjAwfwFdl62l22djfWEyi/3Yyg3rQ6Gxt9vNIDxrx3zqXTqPhgLUYrdASbPSjrsXGx/t3oBGCfXVVvHDBdPRtN5yvSO1LtDmA+fu28/KYSzFp//ezFEIwtV8Go3sm8cLKb/n3xlyW5O3jyRkTGZue4tV77ZUcxbt/vI6X56/lw6+3siW/mD/fN4PYCN90pQ0ND+BPr9zEK88t5uN313OkqJqHnrlSzYbZSapG30karQZni+9qNd9XXtXQ6TVe91VUUd3UzNVDOjY3fpPTwby9ucxOG8hVPft3uByLy9azuGwdM2LH8mrWQ0yKGfmjD/InEkJwScwo/jHkd/QJ7EGaJZE/9rsTvUZHqa2SQSG9eC3rIWocDSwp+446ZyMtbgeatp46AI3OJr4oWcObBz7lmd3/5P3iBfyifzYLC/M51FjLS6Nn4KfT0+CwHz/u4Ig4SqwNp+1tBBDoZ+IPU8fz0W2zCTX7cef7n/HK6g14PN71vDMZ9fzmxvH89f7LKK9q4OePf8jeQxVnTthOOr2WXz44jf974BI2rNnDY/d/iKPlh7vFKmfWfX5l50hyaiTLvsilvraJoBDfdC88kcXfiNXmOPOOp1Fva71Mj7B0rHybjhbjkh6mJXe8+2iZrYp/HvycwSG9uD31ii6ftMwj3TS5yql3FFHnOESj4whu6UDiRkoPEg8SNxr0+OnC8NdFnPQw6yLRiI79PDRCw/S4MSdtCzcG0+JxIITgppRp3JQyjaKmUoxtTVXHgvRXZeupc1q5LfVyUi0JPJf/LlEWPe9NvAa7qwWTzsiB+mpe2fUdo6KTuSK1L58c2ElyYAh1LTYi2tHFtV9cNB/+bBZ/+GI5L636jrzSCp69fBIWk3eD/S4Y2IM3HrmGe59bwB1PfsRz980gK9M3S2YKIbh0VutCJs8/sZDH7v+Qx/46S9XsO0gF+k5K6dl6Y6twfwUDh3p3GdwegWYT1mbv2lO/r97WWvvr6BQH68qKMGi0DIno2KhLj/Tw4t730QgN96TN7pIg75Fuym1bKWpcTpW9gAbnIdzyvydIozYYnTAi0CKEBoEGIbS4ZQu2pqqT9gXQCiOhxnTCjBmEm3oTZuxFoCERjejYvZjhYf3425732Fm3n4nR2QwITkcvdDy1+23MWj/uy7iWgoYiyu01jAzvT6qldVbJouay4wOnvixby6bqXcxMuIjJiRl8cmAnb+zeSLw5iOvSB9EzqP1Xfn4GPX++YjL94qJ49us1XP3Wh7x8zXR6RHi3pkGP+HDeenQ29/15Afc+t4BH75jMxSN8N55k0qWDAXj+iYU8/psPefQvKth3hAr0nZSS1hroi/Yf7ZJAH2A2UlXX1Kk8GuytgT6wg3PWry8vYmhk/A9OunUmi0rXsbN+P/ekzSbC5LtJzaSU1LTs5WDjEgobV2BzV6HX+BNpGkCMfxbBhmSCDMkEGZIwan94sI+UEoenkWZX5fFHneMgVfYC9jcsoqD+PwDohD/R/oOJ9x9BnDkbiz6m3WVN8I/i+UG/4ZuKHA5aS+gT2IM4/0ju7nk1n5espqChkB11+4k2hZJibj2hbqnJJ9UcT4ih9SbtlQkTiDaF8emRVfQJ7MHLYy6lpsWGBtGhwWpCCG7MHkxGVAT3fbyIq978gOeumMz4Xt6NUo0KDeD1R67hgec/55FXFlNd18TsS4Z4XZ4fcizY/+2Pn7cG+7/OxmBQocsb6tPqpJAwC0HB/hTuP9ol+QeYTRSW/ODiXO1yrOkmyOR9jb7K1kRBbSUPDBrboWOX2Sr5Z+FChoT05uLo7A7l8X0e6WJfw5fk186n3nkIDTrizCPoETCJePModBrvTmhCCIzaQIzaQEKMJwc5j3TT4DhMdUsBFfZdlDZt4EjTOqiEYEMKceaRxJtHEmUagBBnvuU1LvLkQYzBhgBuSpmGlJIddfvw05oIM7be2NxWt4dkSyz6tvEDHunhgohBJJpjeLewdS2fSL/Or2I2PCWBT26/ll/O/4L/+3Ahv75oFLddMNSrK69As4mX5szkD68u5oX3V1NntXHnlaN8dvU26dLBeDySF55cyJNz5vPIc9eg/wktQt9Z6pPqJCEEKWlR7Mkr6ZL8A80m6hqbcbk9HZ6uwNrSgk6j6VD6Y/PIZ0d1bIGKfxctRiME96TP8tmP/tujf+JA42LCjX3IjpxDsmX8aWvsnaERWoKNKQQbU0gNvAQpJQ3OQxxp+o6Spu/Ir51PXu08Qo0ZjIz8LWEm75otjk1BIoSg1FZJ/+DWNX/XVW6jztHAqPABBOktSCl5dNdrpJjjqGypJcQQiEu60OGbbr2xwYHMu/UaHvp8KX9bsZ5Gewv3TxztVR5Gg46nfzmNZ/+5grkLN6HRCO6YOcon5QO45PIhuFxuXv7TIp5/YiEPPH65WqqwnVSvGx8YeWFvCvcdpWDnEZ/nndU7gWa7kw07izqcR6/oCFweD9uPlHmdNqqt/3Z5s7VDx3ZKN2GGIMKNvmmycbibKLQuJy1wBlMS3iQj6LIuC/KnIoQgyJBMZshsLo5/iVmpXzEq6vfYXNUsKv45mypfxOlp9iq/Y8Gqb1BP/lO8nPmHl/Je0WKyw/qRHpB0fL/bUq9gb+Mh0gISuTF5Giatb2dKNel1/HXmJVwzpB9vrs/hoy07vc5Dq9Hw4K0TmD4mk3c+28g3Oft8WsbpVw3j+tvHsWLRdpZ+kevTvLszFeh9YOK0gfibjXw+f6PP8x41MIWQAD8WrcnrcB5j01LQazQsyz/gddrM0Cj8dXo2HT3coWNHGIOpaqnDV5PnFTetwSMd9Aycel7U5vQaMz0Dp3JZ0jzSgi4lv24+nx+6jmLreq/zmhA9nDt7XolHevhVxnVcEDGIRud/788k+kfTN6gnOqElUG8+42cqpeTvO9azvLj9wVYIwSNTxjO6ZzKPf7mCbw8c8vp9CCF44KaLyOwRzeOvL6GwpNrrPE7n2p+PZeDQFP7xp0UUHfBdt87u7IyBXgiRIIRYJYTYLYTIE0Lc27b9qrZ/e4QQWd9L86AQYr8QYo8QYlJXFf584W82cvH0gaxZlkdNVeOZE3hBp9MyaWRv1m47SH1jx+YYCTAZye6RyPKC/V4HXL1Gy+CIODZVdOxqJdwYjN3jwOryzfwoRdaVmHVRRJi6dvF1bxm0AYyIfIBL4l9Dp/FnZdkDrCl7FIfbu+9D/+A0ZidNpldgMk6Piy9K1/Be0SKgde57h8eJXuj+Z178U2nxuFlevJ+713zORi9O1DqthuevnEJqRBj3frSI/RXeB2qjQccz907HaNAz54WFne45diKtVsOcJ2biZzbw1O8+wt7J7sc/Be2p0buA+6WUfYBs4G4hRB9gF3AFsObEndtemwVkApOBV4ToYJ+0H5EZ1wzH5XKzeIHvp1ueOjoTp8vN0g0FHc5jQq9Uimvr2Xu06sw7f8/QyHgKaiuoP2GQTnsda7KpapuXvTNa3A2UNm0kyTK+XTc+z4VIv/5MT5zLwNCfU2RdycLDN1Fh874JBECv0TE+ciiVLbX8X84zPFfwL2zuFjICk9t1NWPS6vjnRVcRbwni5ys/YXdN+zsMWExGXrv2Ukx6LXe8/xlVVu97fkWFBvDML6dRUlnPY6995fXArNMJiwhgzhMzKS6s4pXnFvss3+7qjL8WKWWZlHJr2/NGIB+Ik1LmSyn3nCLJpcCHUsoWKWUhsB8Y5stCn4/iEsMYNiqNL/+Tg9Pp25Gy6UkRpCdF8OXa3R3O46JeqQhgWcF+r9MOjUpAAls6UKsPN7ZOvlXlqPM67fcdtq7Bg4uUgK5dsrGztELPgLBbuST+VQQalhy5ix0173Yorzj/SH6dcT2P9b2DKxMmcFfPK+lhaf94hlCTP/+66GosegM3Lv+I4sb2/z/EBgfyyuxLqbY2c/cHC2npwPd6UK94fnXdWNZuO8g7n23wOv3pDMlOZdato/n6820sX7Tdp3l3N15Vi4QQycAg4HSN0XFA8Qn/PtK27ft53S6EyBFC5FRWVnpTjPPWZdeOoLbaymcf+PYLDTBjbF8KCo+yeov3gRog3GImOyWBf2/Mpdra/puFAIPCYwnQG3lt1wavp7qN84tEJ7QsKl3X6Xb6AEPr18jm6vzVwdkQ4deX6YnvkmgZy7bq16lt8f4eyTGRplAyg1LRCI3Xn2OcJYj3JlyD3e3k6S2rvErbLy6aZ6+YzPaScj7I2eFV2mOunDCQyaN6887nGzhc7tv/uxtuH0fmwERe/ctXNDb4bvrk7qbdgV4IYQE+Ae6TUjZ09sBSyjeklFlSyqyIiIjOZndeGJKdSvbYDN57/RvKS337hb7swv70TAjnuXdXdLi986FLxtHkcPLE4pVepfPT6fnD0IvYVHGEd/I3e5U2UG/mZz0uY3NNHl+UrjlzgtMIN/Ym1JjB2qOPUuco6lReZ4tBa2Z4xP0INBRZvfvcf0hHbkL3DA7n5l5ZbcsXetd8N6lPGtkpCby1bjM2h/dzzgghuGf2GPQ6LW988q3X6U9Hq9Ny92+n0tRoZ/7ctT7NuztpV6AXQuhpDfLzpJQLzrB7CXBip+v4tm0/CXc/MAUhBP94drHPepoA6HVafv/zi6mua+bl+R37QqdFhvOLcdks2b2PJXl7vUp7ZWo/Jiak8dy2Neyp9e4KbHrsGIaFZvL2wc84aO34V0GnMTE+5k9ohZGVpXNocXe6vnFW+OlCifIbRFHjCp9+J7x1a+8sTDo9r+zy/orzl+NGUNXU3OFafViQmVmTB7Nswx6fToAGkJoezfgp/fnsg41UlHW+ibA7ak+vGwG8DeRLKf/WjjwXArOEEEYhRAqQBmzqXDF/PCJjgrnxzgvZtG4v61bm+zTvPj2imTV5MJ+u3MHW/OIzJziFn43MIjMmkj8uWkltU/svdYUQPJM9mQCDkV+v/xKH2+1V2vsyriNQb+bZ/LnY3R3vgWHWR3FhzDM0OctZXf4IHtl1M4f6UnLARTQ4D1Pr6FjTmy+Emvy5Nm0gnxfmedVWDzAkKY6RPRJ5a91mmjtQqwe4fkoWAf5GXv3Y+66nZ3LTXeNBSv71mndNUz8V7anRjwJuAMYLIXLbHlOEEJcLIY4AI4BFQoivAaSUecBHwG5gCXC3lLL9UaEbuGzWcFIzonn1ucU0Wb3vqXI6t18xktiIIJ5+Zxn2DvzgdFoNz1w2iUZ7C0985d2PItzPzNPZk8mrOcoL29d5lTZIb+H+jBsosVXwxoEzXRSeXqRff7Ij51DWvJn1R59CyvN/cYok81gEWooaV5zTctyWOQyt0PBanvdjPn4xbgQ1zTY+2NyxG58BZhM3TBvKt9sLyd3j24v8qJhgLp01nOWLtnNwn1qK8Pva0+tmnZRSSCn7SykHtj0WSyk/lVLGSymNUsooKeWkE9I8JaVMlVJmSCm/6tq3cP7R6rTc89B0aqqsvPG3r316ue5n0vPgrRMoLq/j7x+s6VDe6VHh3D0um8W79vDJ1l1epZ2UmM7VPfvzWt4Glhw6VaerHzYwJIOrEibwdfl3fFLcuWaMtKBpDAq7nYONX7Oq7MFO3eg8G4zaIIIMSRy2rvZJfhX2Guqd3o9WjvYPYGZqPz7ev4Nau3c3LwcnxjIqNYm31ufgcHWs7nbNxYMICzLz1qffdSj9afO+ZTRmi5F3X/XNvZDu5PzsjNwN9OobzzW3XMCSz7fyn/d8e6k6rG8SsycP5j/Lt/PO5x0bjfuzUVmM7JHIwwuXsWCbd6Nu/zD0IgaExXDX6k+Zm+/duIHrkqYwMnwA7xR+zuN5b1Dv6PgAs34hNzE47C7KbVtYePgGVpU+RE2Ld/cezgaXp4XV5X+gznGQWLNvJnZ7r2gRd2/5U4dOlhfEJOPwuKm0e3+imN6vF7XNNo7U1XudFloXLZk6ug9bC4506Ir0dAKD/Jl06WBy1u+nucl3A7S6AxXou9BNd41n7MV9eevFZaxe6l3N+UzumT2WKRf04Y1PvuWjpdu8Tq/Xanll9qWM6JHI7z9fysdezGti0Rt5/+LZTEhI47HNy3k6ZyWedgYcnUbLQ71v5c7UK8mt3cMvtj5Lbq13VwbHCCHoF3oDM5MXMCD0VspsOXxx+GaWldzHYevq86L93u6qZWnJLzlkXcmQ8F8wNPwen+S7p/EQGQFJHeqBo21L4+7ASSIxtHVmzeKajgV6gH5psbjdHgoKfT99wfDR6bhcbrZtPOjzvH/MVKDvQhqNht88dhmZAxN57tFPydvesfliTp234Pc/v5ixQ1L563ur+GKN9ycSk17HK7Mv5YKeyTzyxXL+taH9Jww/nZ7Xxl7OjRmDeWP3Ju5ZuxC7u32BVQjB9Lgx/G3Q/fhr/Xh45yvMLVx4fDk9bxm1gQwM+zlXJn/CwLDbqHMUsqrsQf5TeAW51W/R5Dw386HUOw6x6Mht1LTsZVz0U/QNudYn8/M0OpsosVWQEZDcofRaTevP3tsxEQAJIa0D4A7Xdrx3S9/U1nn8d+4v7XAePyRzQCL+ZiOb1p9/V3bnkgr0Xcxg1PPoX2YRERXIY7/6gJJi303wpNNqePLuqQzrm8TTby1jxUbvv9wmvY5/zJrOxF49eXrJN7y+tv0dpLQaDY8Pm8iDgy/ky6J8rl/6IVW29g+V72GJ48XBDzApegQfFy/nge0vUGbr+OA5gzaAAaG3MDP5Ey6M+ROhxp5sr/knnxRdwcrSORxsWOr13DMdVdq8mcXFt+PyNDMp7mWSAi70Wd57GlsnGssITOpQ+s7U6MMt/vjr9Z2q0YcG+RMfGcSu/d7PpnomOr2WIdmpbF6/75x2ZT3fqEB/FgSFmHnypesBeOSeeTTUeTcy9XQMeh1/vncGfdNieOTVxazL9f6S1aDT8fxVU5nWrxfPr1jPCyvWt/tHIoTgjr7DeXnMpeysKefSxe+S58WcKiatgV+mz+LB3rdQYqvg7i3P8nnJNx2u3QNohI5EyxgmxP2NK5I/IjPkOirtu1l79DE+PDiFpUfuJb/uP9S2HMDjww5hNlcNRY0r+ar4LpaV3IufNpQpCW8R4dfXZ8cA2NNQhECQZunY+qzatnmCXB3orSSEID4kqFM1eoC+abHs3FfWJcF42AXpVFc2cmCP6n1zjFp45CyJSwzjsb/N5rd3vcucO+by1Ms3EBYR4JO8/Ux6nr//cv7vmY+Z88JCHrhxPJeP7+9VHjqthmcvn4SfXsdrazexr6Kapy69mGD/9q1KNS25N4mWYG5b9QmXLX6XOzKz+UW/Ee1efvCCiEH0Ckzm73vn88aBBXx25BtmJlzExKjhxxfQ7ogAfRxDwu9icNgdVNrzKG5aw2HrWjZVtg4J0Qg9Zl0kZl00Fn00Zl00Zl0URm0gWmFAKwxohL7trw6HpxG7u54Wdx12dx0t7jqsznKqWwpocrWe4My6aIaG30ta0HT0Gv8Ol/1UippKWVy2nh6WOPx1HVsDuKixddS2UdOxuQYDTUZqmzvXbTgtIYIl6/NpaLITZPHrVF7fN2RE6yphu7Ydomev9i/32J2J8+HyJisrS+bk+H7Wx/PR1o0HePz+DwkONfPMP24kNsG7xZhPx9rcwsP/WMR3O4q4euJA7r12LDqddz9mKSX/2rCNvyxbS7jFzDOXXUx2j/bXHKvtzTyVs5IFB3eRFBDME8MnMSa2/WvpSinZXJPH/MNLKWgsIlgfwOXxFzIpeiQBet8FzQZHMZX2XdQ5DmJ1ltPkKsfqPIrNXQ20/zehE3746yIIM2YQZupFmKkXkaZ+aITv61Abqnfyl4J/4ac18kS//yPZHOt1HlZnC+M+fZ2UwFA+mnSd1/cMWv6/vfsOj+K4Gzj+nTudTuXUe5dQoyN6NWCMMSa4xJ3Yxr2nOMmbuKS9KU5c4uS14zgOcYlxdwAXDMYG08H0JoRAQkgI9XYqp3J13j9ukQWhqIJ0ns/z3HOr2b29Ge747dzs7G/tDiY88zI3jx3Jk1fO7PL7n/SvZVt59aNtbPn3o92+c9rZOJ0u5k34LbfdP5PbH+i9IbP+SAixW0o57nzbqR79BTZmYirPvHIHv/rhO/zkntd46m+3kZrZO70Ok5+R5396LS+9v4l3P99NXnE1f/z+fMKCO3/jaCEEd0wew9ikOP5n6efcuXgpt03I4qezp+Hrff7eeZiPH3+ZNp8bUofzi21fsHDNB8xJSOeJsZeSEnj+g5oQgglhwxkfOozshqN8WPwlbxR+yrvHP2dG5Fjmx15Cqql7tzXsKNA7gUDv/96P02Wj2VGF3dWMU9pwSTtOadOWHXjrA/DRBzXCGpkAACAASURBVGHUBWPUB3X5/rTdIaVkScka3iz8jDRTAr8cdm97VtCuWpSznZq2Fv516Q3dOjG850QZVoeTKandGzY6ydzYSpDJp9eDPLjz1fv6eff6xYoDmerRXyTFhdU8+chbNFva+Ps7D/Zqzx5g1ZZc/vT6avx9jfzxB/PJyux8atuTWm12/vLVZt7avo/ksBCevvYKshI6f1Bqczp4NWcH/zi4DavTwcLBY/jhyKkEG7v2U73AUsKKsk2sr9qF1WVncGAy82MuYVpEVvuNsz2VzWXnb3nvs7ZqJ9MjxvCjjO/h082hrIqWJmZ+9E9mJ6Tz0vRrurWP59ds5o2tu9n22EOYjN0fUnvixeUcK63lg2fu7PY+zuXWK59nzKRUfvqba/tk//1FZ3v06mTsRZKYEsH//ftebrxjKjHxvXM/1Y7mTh3Ca/+7AF8fAw//8UPe+3x3l098+Xob+MWVl/Lvhddjczj43usf8NevtmBzdG4apY/ei++PnMK6797PjWkj+Pfh3cz46J+8nruzS7lyUk3x/DBjAW9O/D33DfoujfZm/nzkLRZu+zV/z/+QQw3HPHKGRZ2tkSf2/421VTu5LWkePx98R7eDPMBf9m3CKV38fPSMbu/j62PFZMXH9CjIA5gbWwgN7N3zFx35mYyqR9+B6tF7OEuLld8tWsWG3QXMGp/O43fNJiig6ye/mtqs/GnVBpbtyyEjMpwn587o0tg9QK65iqd2rWVzeRHJASHcN2wC1w0ajm8nT9ie5JIu9pmPsLpyO9trs7G67ET5hDE1fBQTQocxJHAQXt080dgflLfWsL5qF5+VbaLV2cZPMm9jWsToHu1zW0UxC758l7uHjOdX47t345bqpmamP7+IH1w6mYdn9OwK3xt/9gbpiRH88Qfze7Sfs3n0rlcx+hh45h939Mn++4vO9uhVoB8gjh4u7/YMAiklb6/cxSv/2UKAn5Ef334pcyZldmuMdu2RAv6wch1lDU3cMWk0T8yd2eW6rCst4C/7NnGwrpJgbx8WZGSxMHMMMf6BXa5Pi6ONr2sPsL5qFwfq83FIJ0adN0MCUxgelMrwoFQyA5Px7udDPI32ZjZW72Fd1U4ONxYBMCo4g/sGfZeULtxR6kyWFGTz5NeriPMP5KN5C7s8dAbgckkefPdjthWe4OOHbmNQePeHGgtO1PC9JxfzyM3TWDi/b24+d891L5KYEsFvnl/QJ/vvL1Sg9yCfLdnJS0+vYNplQ7n5zmmkD+n6bAuA/OJq/vTaanKOVTBpRBKP3Tmb2MigLu/Hanfw9o59DImOYErq2S/aabHZ2V1cyoSkeIyGU8/7SynZWVXCG7m7+OJEHgK4Mmkwt2eOZkJkQrcOQi2ONvbWHyG7Pp+DDQUUNZchkXgJPRkBSaQHJJDiH88gUxyJftEYdBdvLkKLo43cxkJyGgo42FDA4aZCnNJFkl8Ml0aNY0bEWCJ9enbeps1h57m9G3ktdydTopN4eca13QryAK9t2cVzqzfxm+/MYsH4UT2q1+//9QVrth3h0xfu6/WplQCtLVa+O/1P3Hb/DG67X826ARXoB4QHb3mZB396JTVVjby9aD233jeDy+dndWtfTpeLpWv284//bMbpktx33WQWzB3bJ7MfDpZV8uyXGzlQUsHfF1zN1LMcFE5Y6ll8eA/v5++nyW4l0RTMDWkjuH7QcOJMXT8QndRkb+ZQ4zEONhRwqOEYhc1lWF02ALyEngS/aJL9Y4jxCSfaN5xonzCifcIJ8Q5A10s3H3dKFzVWM2WtNZS3VnOipZJDjcc4ZinBhUSHjrSABEYGpzMjYiwp/rG9kiZhd1UJP9u6kmONdSzMHMOvxl+GoZvDWftOlHPbGx8yK3MQL9w0v0f1q61v5pofv8rVM4bz8zv75t6/OfuL+cndr/G/f1nA5BmD++Q9+gsV6D3Ex+9tY9m7X7N4+Y/by6xtdow+BqSU3f5PV1nbxHOL17JpTwEZSRH8/M7LGJHWvV8KZ2NpsyKE4Huvf8ALN80nOSzklDqfXv8Wu41VxXn8p+AAX1cUI4CpMcntd7fyN/TsBKBTuihvreaYpZRjzSUcs5RS3FJBjbUe2WHuvLfOQIghgECDiQCDH4Fe/gQY/Anw8sNL54VOCHTo0Aud+x6uSJodrbQ42rA4WmlxttLsaKPGaqairRZHh6tvjToDGQFJDNOGlQYHpuCr770pmq0OO3/eu5HXc3cS6x/I05Ov5JIuXMdwuqomCzf96z30Oh0fPXArgb7du0jrpH8u3cIbn2znw2fvIjG69ychAHz64Xb+/sxK3lrxEyKju99RGAjUPHoPkZwWRWpGND+55zXu//EVDB4ej8Hb3TPrGCRdLhc6Xed7oVFhATz36NWs33WU599ay72/fZ+5U4fw8E3TiArtnSt2TT5GNuYX4udtIDks5L/qnFtRzZ9WbWBMYixzh6YzJCaS61KHc13qcE401bP02EGWFGTz6OblGPVezIwbxLzETGbFpxHg3fXgqBc64v2iiPeLYjpj2svtLjtVVjMVrbVUtNVQ0VaL2dZIk72FRoeFstZqmuwtNDvPnb/dR+eNv5cvfl4++Ot9SfSPYWLYCOJ8I4jxjSDWN5xQ76Be+7Vwuu2VxTy29XOKmszcljGax8fOxGTo/kGkze7g++8vp7HVyjt339TjIN9ms7N0zX4uGZ3aZ0EeoOBIBQFBvkREdf2cj6dSgb6fOhm4s8ankDU+hU8/3M6OzXkMHh6PTqdr7w23tljZt7OQTWtySEyJ4Ja7p3f6PYQQXDo+nYkjknhz+Q7e/Xw363bmc/Oc0SycP54A/579xwbYdLSI8UnxgHvY6GTmRIfTRUF1HS7pwqDX8dSq9VySlsz908YjhCAhIJhHR03jhyOnsquqhJXHD/P58SN8UZyHQadjUlQSs+JTmRaTTFpQWI+GEww6A3G+kcT5Rp5zO6d04ZJOnFLiki5cuHBKFzoEfl4+6MWFn+nTYGtjRdFhlhZks7u6lERTMO/OWcCU6O4lPDupxNzAT5esJLu0gpduuZohMef+t+mM1z/eToOlje9dObbH+zobl8tF9h536oPeGALzFCrQ91MVpfWEhPnj6/dNj6y6shEpJS6XRK/X4bA7+fDNLZworGb65cNZ9ckeJBtZ0IVgD+Dn481DN07jmhkj+OfSLby1YicfrzvAwqsmcMNlWfj6dH3GisslabHZOFBSwS/nuU+ICb75j9dss3GwrJLbJmRx5fBMvj9zMs1WG0KI9oOY0+VCIJgQlcCEqAR+PX42e6pLWX0in9Un8vntzjUARPqamBKdxJSYJKZGJ/VoXP9c9MI9XHOx5+84XS42lRextCCbL0/kY3U6SAsK44kxl3J75mj8ejjEtSL7CL/5bA0CwV9v/A6XDU7tcZ2/2JrLm8t3cM3MEYweHN/j/Z3NpjWHKC2uZeFDs/rsPQYiFej7qV1f5/PJ+9u59d6ZJKVFcvhgKakZ0djtTry93R/b5x/tpr7OwoJ7ppOaGcOgjCje+PtX2GyO9m26IjYyiN8+NI9b543n5Q838dL7m3h7xS5uuWIMN8we1aUevk4nqGyy4JSSEXHR7WUnNbVZ+fpYMftLyvHS65mRnoy/dhHOyZ6Y/rShKJ0QjIuMZ1xkPE+MvZTipnq2lBexpeI4m8oL+bjQfaesOP9AssJjGR0RS1Z4LMNDozqdXK2/qm5tZkt5EZvKC9lYVkh1azNB3j7cnDaS61NHMDIsusc9WIvVxh8/X8+yfTlkxcfw5+uvJD6k5wfNbdlF/G7RF4wZEs/P7ui7AOxyuXj31Q0kJIdzyWVD++x9BqLzRgMhRAKwGIjCne1pkZTyBSFEKPABkAwUATdJKc1CiJnAJ0ChtotlUsrf9X7VPdvVN01kyIgEFv9jLV4GPVkTBjF99rD2AG5pamXn1ny+c/14EgdFAPDViv14eenx9vZq7xW7XC6EEF0KAhlJEfzfz67jQF4Z/16+nVeWbGHxZzu5YfYobpk7hrCgc+fOya+q4c2v91JtaWbYWX7yRwcG8OYdN7CtsJhPD+QSGeDPqHj3dQKrc4/yWfZhwk3+3DJuBOmR4Wc88ZwYEExiQBYLMrJwSUlefTVbyo+zp7qUfTVlrDh+GAAvoWNwSASDQyLJDA4nIziCzJAIonxN/fLnvZSS8pYmcs1VbK8oZmN5IYfN7jz9wd4+TI1JZn7yYGbFp2HU97yv5nJJPj2Qy/NrNlNjaeah6RN5ZMakXpmJdfBoOY+/sJyUuDCe/dHVGLqYZK8rtqw7TFFBFY/94Xr0fTCLbCA776wbIUQMECOl3COECAB2A9cCdwJ1UsqnhRCPAyFSyse0QP8/UspOX/KmZt2cm6WpFVOALxu+PEjakBjiEsLYtvEIe3cc4/pbJxMZE0y9uZk/PbmE2+6fyYjRSZSX1BEU4o+fv3vopyczdPKOV/Hm8h18tSMPby8986cP5+YrRpMUc+Z53harjY/25bAmt4B9JWU8NmcGk1ISiAsOxGjwwuWSp/Tu396+j01Hi/jnrdeybG8OXxzK59nr5rI69yg7ik7w1DVzMOj/O0B8cSifLw/lE+Trw0PTJxIRcOoBqKrVwr7qMvbVlHOgtpwj9dVUd7gxSoDBSHpwOAmmIBJMwdpzEAkBwUT5BuB9hvfsTQ6Xi8qWJsqaGylqMpNrrnI/6qqot7kv3/fW6RkXGc/UmGQuiUlmWGjUf/3S6Yns0gr+8Pl69peUMyI2il/Ou7T9gNtTx0preeAPHxDoZ2TRr27pUnK9rnK5XDz8vVew2xws+s/3vzWBvtdm3Ugpy4FybblJCJELxAHXADO1zd4E1gOPdbO+yjmYtJQFsQmhVJSYiUsIw8/fSF1NE+HazIKlb20lY0gsAQE+rP38AEcPl5O99zhZ41K485HLevTFz0iK5Knvz+eBcjNvfraDTzccZOlX+5k8MpmbrxjNxOHJpwRuk9Gb2yeO5vaJo2m22ihvaKKo1symo0V8b8Io8iprCPAxkhjqzsCYU17J6IQYTtTVs+loEYcrqnnuy00khAZhczjJKasiKyHmlAPE1oLjvLJxOz++bCrrjhxj6d4c7pk6FoNeT0F1LakRYUT6mpiTmMGcxIz2utW1tZBXX0N+fQ1H6qspaKxld3UpnxXl/tcdl4K8fQjz8SPcx48wH3/CfPzwN3jj52XAV3v4eRkw6r2QEuTJSZrS/Wx1OrDYbVjsVprtNprsVhptVspbmihvbqSy1XLKvXZ99F5khkRwZdJghoZEMjQ0kqGhUV1OEdEZhTVm/rlpBx/vP0S4vx9/vGYO144aesrn2BPHy+v44TNLMej1vPjY9X0a5AG2rj9MYX4lP/vddd+aIN8VXfrdJ4RIBkYD24Eo7SAAUIF7aOekyUKI/UAZ7t59zhn2dT9wP0BiYs9Snn5bdLwiVghoMLdQX9dMyfFaNq89xB9evI0Nqw+ycXUOl80bxd8W38/f/vQZm786xIw5p97lqDs9/MSYEH513xU8fNM0Plp7gGVfHeDR5z4iKSaEGy8fzbxpQ/H3PfVEoL/Rm7TIMNIiw9rLyhua+MUnqwn0NZIWEUZ+VS0PXDIBIQReOh1v3XUjZQ1NrMrJw6DXo9eCz8kgdKSyhnV5x7hr8limp6eQFhHGXYuX8uD0CdidTp5bvYnKRgtpEWE8cMmEU9471MePSdGJTIo+9Ttndzkpb27ihKWeE5YGqlot1LY2U9PWQk1bM3kNNdRVttBst2Hrxt2vfL0M+Ht5E+htJMrPxJSYJGL9Aon1dz/iTUEkB4T0am/9dC02O18cymPZ3kPsPF6CQa/n7iljeXj6REw+vTeXf9WWXJ5+Yw1Gby9eevwG4iK7l1K5syrKzLz41HKSUiO59IrevZuXp+j0BVNCCBOwAXhKSrlMCFEvpQzusN4spQwRQgQCLimlRQgxD3hBSpl+rn2roZvuef/1jaxYuouJl2QwZGQC0y8fxj+fX0VUbDA7NucTHhlIXU0Tc64ezWXzRp0xuB/OLiF9SAz6boyd2h1Ovtqexwdf7uHQsUp8vL24bGImV80YRlZG3HkPJAdKKsitqOLyIWmE+vtRa2nhgXc/5t8Lrz8l8GSXVpBXWcOo+BjSIsP4z+5sis0N3DB6OElhwXx5KJ8N+YX8et6s9lQLljYrb23fR31rG0/M7X62xjNxuly0Ou20OOy0OuxYnQ7EyTlFwv0shMCo02PyNuLv5Y1XHwbwc5FSsqe4jGX7cvg8J48Wm52k0GC+mzWUG8YMJ9zUez3t2oZm/vr2elZvO8KojDh+/8i8Xrsm42xaW6z85J7XqSyr58XF9xGfFN6n79ff9OoFU0IIA7AUeEdKuUwrrhRCxEgpy7Vx/CoAKWXjyddJKVcKIV4WQoRLKWu63gzlXG65ezrX3ToZvV6H3ktPW6uNY/mVLLhnOjcunMbq5fvYvjmPgED30I+UEpfThd5LT35uGetWZVNwpJyyE3Xc+chlXDavazlMDF565k4dwtypQ8gpKOeT9QdZve0IKzblEB8VzFXThzNv2hAiz/KffWR8NCPjo9v/DjP5ccOY4dzy2vsMjYlkRvogxiXFERlg4uP9uSzZe5Bfz5tFSX0jcUEBRGpj8kera0kMDabFbsdo8KKuuYVQfz/iQwLZX1qOxWrrcVrdjvQ6HSadsUcXI/WlFpudbYXFbMovYkN+EWUNjfgZDMwdlsF1o4cyNvH8B+GucLkkyzce5G/vbaTN5uD+66dwx1UT+iStRkdOh5M/PrGEoqOV/O7/bv3WBfmu6MzJWIF7DL5OSvloh/LngNoOJ2NDpZQ/F0JEA5VSSimEmAAsAZLkOd5I9eh7h93uaO/R37hwWnt5fm4ZSamR7TN2aqoaee3F1SSnRXLjwqnkZpew8cuDPPg/V/Y4ALS22Vm3K5/lGw6y53AJQsDozHhmTUhn5rh0IkJM591HZaOFNYeP4nS5uC5r2Cm9+5MJ1aSU3DttPM1WG79bsZZZg1OZMyQNIQQPvfsJB8sqyUqIYc6QdOYNz+jTIZGLzeZwkldVw67jpWzML2Tn8VLsTid+BgOTByUye0gqc4akt09f7U2FpbU8/cYa9h0pZczgeB6/e/ZZT9L3JiklLz29gs+W7OQHT8xn/g3j+/w9+6Pe7NFPBW4HsoUQ+7SyJ4GngQ+FEPcAx4GbtHU3AA8JIRxAK3DLuYK80nsMBi9uuH0q/3rhSx646e/cdOc0Jk3PpLqykb/+/hPGTU7j7h9czqcf7iAsMoDZ3xmFTqfD39/Inh3H2nv7Tqer2ye0fH0MzJs2lHnThnKi0sznm3NZtzOfPy9ex58Xr2Nkeiyzxqczc3w6MeFnvkQ9KtDErRO+SdompcTpkuiEwGhwTx2ttrhnz6w8eIRmm42s+G+uhPzH965h+YFcdheXcdXIcye16slspIvB4XRRbK4np6ySA6UVHCitJLe8qv1GLqnhodw2IYvp6cmMTYzF26tvLpVpbbPz1oqdvLl8B34+Bn5x7xyumj7sgv1bLnlrK58t2cmNd0z91gb5rlBJzTzUkZxSvAx6UjPcQyMVZWb27yxk+OgkXntxNdffPoUhI9zpFF56ZgVGoxf3PXoF4P5lUFpcx9uL1nPHQ7NISO75T+LC0lrW7cxn7c588ovdc8IzkiKYOS6dS8elkRLX+TQGhyuq+d/PvqLZaiM5PISbxozgkvTkU7bJKavkre37ePyKGQT7nf1Cr+zSCu59+yMSQoJICAkiXnuOCQwgIsCfcJMfoX5+vTYbpTMsVhvVTc1UNVkoMTdQWGumqNZMYY2Z4rp67C4XAL4GL4bFRDEiLpqRcVGMio8hNrhv87uYG1tYumY/S9bsw9zUyhWTB/PorTMJDeq7u0V1JKXk4/e28crzq7hk9jCe/NMNXcrx5GlUUrNvucxh39yswuVyER0bQvQ1IRzOLiEkzERIqAmdTkdhfiUVpWbu0C4ZryyvZ8XSXVSWmSnMr+DA7sJeCfQpcWGkxIVx97WTKK4ws3F3ARt2H2XR0q0sWrqVxOgQZo5L45LRqQxNjT7n+O7g6Ajev/cWsksriNYCcom5gQ92HWB6egrjk+NZe+QYJqM35pbWcwZ6k9HIvGEZFJsbOFRexercozi0QHqSXgjCTH6E+/sT5GvE5GMk0MeIyWgkwMcbf29vvL30eOl0GPR67eGuv9PlzovjcLlwuiQOl4tmqw2L1YbFanU/t9mob22j2uIO7i02+ynvb9DrSQoNYlB4KLMyB5EcHsrwmEhSI8L6fBz8pOPldby3ag8rN+VgtTuZmpXCnVdNZGRG72Y8PRe73cFLT69g1cd7mDJzMD/77Xe/1UG+K1SP/lviZJK04sJq/v7syvZbrP32p+8xcmwyo8anUJRfxea1hxg1PgVfX2/ycsu4+c5pRET1XarXarOFjbsLWL8rn925J3C6JP6+3owflsjE4UlMGpHcqZujNFttvLltD9sLS2hqs5IUFszdU8a2p1/oLIfTRUVjE1VNFqotLVQ3NVNtaabG0kyNpYXGtjYsbTYa26w0Wa3/FZQ7S+A+yJiM3ph8vAn0MRIZYCIywJ8Ik3/7cmxwIHHBgRflHENrm50Nu4+yamsuXx8owtug58qpQ1gwdywpcWHn30Evqigz88wvl3Jo/wkW3DOdhQ9eqoI8Kh+9chZV5fU8/9uPCQz2IyE5nB2b83n2n3fy0tOf4W008Mhj82hrtfPuqxuIiQ/h6psmXrC6NVha2ZVzgu0Hi9iefZyK2iYA4iODGJUZT1ZGLCMz4kiKCTnnME9dcwsuKQk3+ff5GLzT5aLFZsfhdGFzOrE7ndi1ZQHodQK9ToeXTodOuJf9jd74GQwXdDiosxxOFzsOHueLrbls2F1Aq9VOdFgA37lkGNfPHnXe9Bd9Yf0X2bzw1HIAfvTLq5k5R82VP0kFeuWsnA4n772+ieS0SFIzoomJD2Xj6hze/td6YuJDGJQejbXNzu0PzDwle+aFJKWkuMLMjoPH2X6wmAN5pTRY3GkBgkw+jEyPZXhaLINTIhmcHEVwN254rrg1WFrZmVPMtgNFbN5XiLmxhUB/I7MmZDB3yhBGZcRdlINSS7OVl59dyerP9jFkZAKP/+F6ouP6Lo/9QKQCvdItLz+7klWf7CFrfAq/+79bu3xDk75yMvDvP1LK/vwyDuSVUVxhbl8fHRZAZnIkmclRDEmJIjM58qL0PgcCm91BbmElOw4e5+sDReQeq8QlJQF+RiaOSGLO5MFMHpmMt+HincLLzT7BM79cRmWZmQX3TOfWe2d066I+T6dOxipd1tZqIzktkjlXZZE+JJZ6czPBIWcOlu++uoGmxlZmz89qn9nTl4QQJMWEkhQTytUzRwDunmj+8Wpyiyo5UlTFkaIqNuwuaH9NRIg/mUnuoJ+ZFElKfBixEUEX7ARmf1FTbyE7v5wD+WVk55dxuKgKu8OJTgiGpkZz97UTmTQimSGDzn0S/EKoKDOz+JV1rF15gPDIQJ5ddBcjRvfsJiqKCvTKaex2J1kTBjFt1rnzeVdXNfLlJ3tZ9s7XpGZGM3t+FjMuH05YRN9e8t5RkMmXccMSGTfsm7w1llYr+cerOVxUxRHtALB1f2F78jCDl57E6GCSY8NIjg0lKSaE2IggYiICCQvyH1Bz6k/X2manqKyWgpJajpXWcKykloKSGqrqLAB4G/QMToni5jmjGZkeS9bgOIJM/WPIq8HczPtvbGL5hzsQOsGNC6ey4J7p7dlXlZ5RQzfKf+nscE1jfQvrv8xm9fJ95B0qA2Dw8HimzBzM5JmDSUyJ6Ouqdkqb1c7REzUUltVSVFrH8fI6CsvqKKtqOCV7pNGgJzo8kNiIICJDTYQF+xMeZCIs2M+9HGwiyOSDr9FwwQ8IDocTc1Mr5sZW6hqbqaxtory6kfKaBspqGimvbqSm3sLJ5ngb9CTHhjIoPpzMpEhGpMeQmRR5UYdjzqSt1cayd7/mP29uoa3VxpyrR3Pb/TP7dKaXJ1Fj9MoFVVxYzea1h/h6wxHyckoBiE8KZ/LMTMZOSmPYqAS8jf3rLk9Wm4PS6gbKqxsoq26krLqB8hr3c7XZgrmxhTP99/DS6wjw9yHI5EOgvw/+vt74Gg34GA34Gg0Yvb3wNRoweOnR6QQ6beaNXifQ6XQ4XS6cThcOp/vZ6XJhsztpabPR0mY/5bnR0oa5sYWmFut/1UOvE0SGBhATEUhMeBCxEYGkxoeTGh9ObGT/HqKqq2li5bJdfLZkF+ZaC1NmDuau78/uN52DgUIFeuWiqa5sYNuGI2xdf5j9uwpxOl14G70YOiqRMRMGkTVhEGmDY/p93nCH04W5sYXahmZq6pupq2+mobmNRksbTS1WGi1tNDa3YWmx0mq1Y7U5aLXaabPaabM5uvReBi89vj4G/H3cBw0/X2/8jAYCTT4EB/gSEuhHaKAfIYF+BAf6Eh0WSESIqV8H8zM5nF3CJx9sZ+PqHBwOJ+OnprPg7ukMy1KpyrtDBXqlX2hptpK95zh7dxSwb0chhUcrAfA3+ZA1IYUJU9MZPzWdsIi+vXT/QnO5pLvn7nLhcsn2v0/ePMVLr8dLr3NnHtV17VaPA01zUxubvsphxbLd5OWU4udvZM5VWVx10wSVcbKHVKBX+iVzrYW9O46xf1chu74+Sk2lO6t1amY046emM3pCKkNGxGP06V/DPErXOOxOdn19lK9W7mfbxiPYrA4SUyKYf+N4Lp+fpU6y9hIV6JV+T0pJ0dEqdmzJY+eWfHL2n8DldGEw6MkYFsfIscmMGJPMsFEJ+Pj2fopdpXc57E5y9hezdV0u6744SIO5maBgP2ZcMZzL5o0ic1jv5sFXVKBXBqDmpjay9x4ne08RB/Yc5+jhclxOFzq9jpS0SDKGxpExNJbMYXEkDYrEy6AuoLnYPC27iQAADOpJREFUaqsb2bklnx1b8tm7/RgtzVYM3l5MuiSD2fOzGDc5TX1OfUgFemXAa2m2krO/mIN7j5OXU0ZebhmWxlYAvI1eDEqPJjktkpS0KJLTokhOizzrBV5Kz0kpqSg1c+jACXIPnODgvmIK893nXMKjAt3nW6akkzVhkBqauUBUoFc8jpSSspI6d9A/VMrRw+UUHa2isaGlfZuQMBMJyeHEJ4URlxhGfFI4gzKiiYgKVMMGXdRgbiYvt4xjRyo4klPKoQMnMNe6L77y8zeSOTyOMRNTGT8lneS0SPXvexGoQK98K0gpMddaKDxaxfGCSgqPVnGiqIbS47WnHAACg/xISo0gMSWCpEERJGjPoeEB3/oAJaWkrsZCcWE1x/IqyDtUypGDpZSXfpNLKCY+lKGjEhg6MoGhoxJIGhTZ76fHfhuoQK986zXWt3CiqIaCvHIKjlRworCG48eqsDS1tW/j528kJj6E6LgQYuJOPocSGRNEWEQA/qaz37RkoGltsVJRWk9leT3lJXUUF1Zz/Jj7cXJIDCAyOoiMYXFkDosjY2gcaYOjMansoP1SrwV6IUQCsBiIAiSwSEr5ghAiFPgASAaKgJuklGbtZuIvAPOAFuBOKeWec72HCvTKhXLyF0DxsWqKi6o5UVRDRWk9FaVmykvN2E+70MnXz5uwiEDCIwMIiwwkOMSfoBA/goL9CArxJyjEn8AgX/xNPvibjBi8vS7oLwSH3YnF0kZzUxuNDS2Ya5sx1zZpzxbMtRaqKxuoKK0/5RcOgCnQl6RBESSlRpI8KIKkQZEkpUYSEnb+G7gr/UNvBvoYIEZKuUcIEQDsBq4F7gTqpJRPCyEeB0KklI8JIeYBP8Ad6CcCL0gpz3n3ChXolf7A5XJhrrVQVmKmuqKB2upGaqqaqK1qpKba/dxgbsFqPftdpby89PibjPiZfPDxNWA0GvA2euFt9Gpf1ut16PQ6d3oE7YIphEC6JC6XC5fzm4urHHYnVqsdW5vD/Wx1YG2z09JspamxFWvb2esSGORHSLiJ8IgAouJCiI4Jdj/HBhMdG0xQyMBO4qb0YppiKWU5UK4tNwkhcoE44BpgprbZm8B64DGtfLF0H0G2CSGChRAx2n4Upd/S6XSERQSe9yrdtlYbDfUtNJibaTC30NjQQovFSrOljZZmK83aclurHZvVjs3moLGhFVtbI1arA5eW38bl/CawSyQ6na49N45Op0OnFxgMeryNBoxGL7yNBvxNPhiNXu5fEAE+mAK+eTYF+BIabiI41J/gUH8M/SyBmXLxdOmbIIRIBkYD24GoDsG7AvfQDrgPAic6vKxEK1OBXvEIPr7e+Ph6ExUTfLGroiid0unT5kIIE7AUeFRK2dhxndZ779JZXSHE/UKIXUKIXdXV1V15qaIoitIFnQr0QggD7iD/jpRymVZcqY3fnxzHr9LKS4GEDi+P18pOIaVcJKUcJ6UcFxGhUpMqiqL0lfMGem0WzWtArpTyLx1WfQrcoS3fAXzSoXyhcJsENKjxeUVRlIunM2P0U4HbgWwhxD6t7EngaeBDIcQ9wHHgJm3dStwzbo7inl55V6/WWFEURemSzsy62QycbQ7WZWfYXgKP9LBeiqIoSi9R1zAriqJ4OBXoFUVRPJwK9IqiKB5OBXpFURQPpwK9oiiKh1OBXlEUxcOpQK8oiuLhVKBXFEXxcCrQK4qieDgV6BVFUTycCvSKoigeTgV6RVEUD6cCvaIoiodTgV5RFMXDqUCvKIri4VSgVxRF8XAq0CuKong4FegVRVE8nAr0iqIoHu68gV4I8boQokoIcbBD2SghxNdCiGwhxHIhRKBWniyEaBVC7NMer/Rl5RVFUZTz60yP/t/A3NPKXgUel1KOAD4CftZhXYGUMkt7PNg71VQURVG667yBXkq5Eag7rTgD2Kgtrwau7+V6KYqiKL2ku2P0OcA12vKNQEKHdSlCiL1CiA1CiEt6VDtFURSlx7ob6O8GHhZC7AYCAJtWXg4kSilHAz8B3j05fn86IcT9QohdQohd1dXV3ayGoiiKcj7dCvRSysNSyjlSyrHAe0CBVm6VUtZqy7u18oyz7GORlHKclHJcRERE92qvKIqinFe3Ar0QIlJ71gG/BF7R/o4QQui15UFAOnCsd6qqKIqidIfX+TYQQrwHzATChRAlwG8AkxDiEW2TZcAb2vJ04HdCCDvgAh6UUp5+IldRFEW5gM4b6KWUC86y6oUzbLsUWNrTSimKoii9R10ZqyiK4uFUoFcURfFwKtAriqJ4OBXoFUVRPJwK9IqiKB5OBXpFURQPpwK9oiiKh1OBXlEUxcOpQK8oiuLhVKBXFEXxcCrQK4qieDgV6BVFUTycCvSKoigeTgV6RVEUD6cCvaIoiodTgV5RFMXDqUCvKIri4VSgVxRF8XAq0CuKoni48wZ6IcTrQogqIcTBDmWjhBBfCyGyhRDLhRCBHdY9IYQ4KoQ4IoS4oq8qriiKonROZ3r0/wbmnlb2KvC4lHIE8BHwMwAhxFDgFmCY9pqXhRD6XqutoiiK0mXnDfRSyo1A3WnFGcBGbXk1cL22fA3wvpTSKqUsBI4CE3qproqiKEo3dHeMPgd3UAe4EUjQluOAEx22K9HKFEVRlIvEq5uvuxt4UQjxK+BTwNbVHQgh7gfu1/60djwH4KHCgZqLXYk+pto48Hl6+8Cz2pjUmY26FeillIeBOQBCiAzgO9qqUr7p3QPEa2Vn2sciYJG2j11SynHdqctAodroGTy9jZ7ePvh2tPF03Rq6EUJEas864JfAK9qqT4FbhBBGIUQKkA7s6I2KKoqiKN1z3h69EOI9YCYQLoQoAX4DmIQQj2ibLAPeAJBS5gghPgQOAQ7gESmlsy8qriiKonTOeQO9lHLBWVa9cJbtnwKe6mI9FnVx+4FItdEzeHobPb198O1o4ymElPJi10FRFEXpQyoFgqIoioe7IIFeCJEghFgnhDgkhMgRQvxIK88SQmwTQuwTQuwSQkzQyoUQ4kUtlcIBIcSYC1HP7jpH+zwmVYQQwkcIsUMIsV9r42+18hQhxHatLR8IIby1cqP291FtffLFrH9nnKON39faIYUQ4R22H1DfUzhnG9/RvosHtbQnBq18QLXxHO17TSs7IIRYIoQwaeUD7nvaLVLKPn8AMcAYbTkAyAOGAl8CV2rl84D1HZY/BwQwCdh+IerZB+3bCczQyu8Gfq8tDwX2A0YgBSgA9Be7HedpowBM2rIB2K59Nh8Ct2jlrwAPacsPA69oy7cAH1zsNvSgjaOBZKAICO+w/YD6np6njfO0dQJ4r8PnOKDaeI72BXbY5i+4U7gMyO9pdx4XpEcvpSyXUu7RlpuAXNxXzErgZC83CCjTlq8BFku3bUCwECLmQtS1O87RPo9JFaF9FhbtT4P2kMAsYIlW/iZwrbZ8jfY32vrLhBDiAlW3W87WRinlXill0RleMqC+p3DONq7U1kncU6LjtW0GVBvP0b5GcP9CAXxxf3dhAH5Pu+OCj9FrP41G4z7SPgo8J4Q4AfwZeELbbMCmUjitfR6VKkIIoRdC7AOqcB+4CoB6KaVD26RjO9rbqK1vAMIubI277vQ2Sim3n2Nzj/gcO7ZRG7K5HVilFQ24Np6tfUKIN4AKYDDwN23zAfk97aoLGui1cbGlwKPaEfYh4MdSygTgx8BrF7I+ve0M7bsbeFgIsRv3kE6XU0X0J1JKp5QyC3dvbwLu/zAe5fQ2CiGGX+w69bbztPFlYKOUctPFqV3Pna19Usq7gFjcv7hvvohVvOAuWKDXegpLgXeklMu04jtwX3AF8B++Gb7odCqF/uJM7ZNSHpZSzpFSjsU97lmgbT7g2teRlLIeWAdMxv1T/uT1GB3b0d5GbX0QUHuBq9ptHdp4eorujjzlc5wLIIT4DRAB/KTDZgO2jWf6DKX7As73+WYYdUB/TzvrQs26Ebh767lSyr90WFUGzNCWZwH52vKnwELtjP8koEFKWX4h6todZ2uf8KBUEUKICCFEsLbsC1yOu2e0DrhB2+wO4BNt+VPtb7T1a7Xx337rLG08fI6XDKjvKZy9jUKIe4ErgAVSSleHlwyoNp6lfUeEEGlamQCu5pvPdcB9T7vlQpzxBabhPvlxANinPeZp5btxz0DZDoyV35w5/zvuHnA2MO5C1LMP2vcj3DNw8oCn0S5Q017zC619R9BmHvXnBzAS2Ku18SDwa618EO6D1FHcv8qMWrmP9vdRbf2gi92GHrTxh7jHph24OyevDsTv6Xna6NDacfL7e7J8QLXxTO3D3aHdotX/IPAO2iycgfg97c5DXRmrKIri4dSVsYqiKB5OBXpFURQPpwK9oiiKh1OBXlEUxcOpQK8oiuLhVKBXFEXxcCrQK4qieDgV6BVFUTzc/wO9sMiLQmwofQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np  \n",
    "from scipy.stats import multivariate_normal\n",
    " \n",
    "x, y = np.mgrid[280:340, 190:230]   \n",
    "pos = np.empty(x.shape + (2,)) \n",
    "pos[:, :, 0] = x   \n",
    "pos[:, :, 1] = y\n",
    " \n",
    "irlidar = multivariate_normal(mean=d.mean().values.T, cov=d.cov().values) #2次元ガウス分布を作る\n",
    "cont = plt.contour(x, y, irlidar.pdf(pos)) #密度の値の等高線を作る\n",
    "cont.clabel(fmt='%1.1e')                          #等高線に値の文字列を入れる\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
